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  1. Ngeow WC, Atkins S, Morgan CR, Metcalfe AD, Boissonade FM, Loescher AR, et al.
    Neuroscience, 2011 May 5;181:271-7.
    PMID: 21377512 DOI: 10.1016/j.neuroscience.2011.02.054
    We have investigated the effect of three potential scar-reducing agents applied at a sciatic nerve repair site in C57-black-6 mice. Under anaesthesia the nerve was transected, repaired using four epineurial sutures, and 100 μl of either triamcinolone acetonide (1 mg/100 μl), an interleukin-10 peptide fragment (125 ng/100 μl or 500 ng/100 μl) or mannose-6-phosphate (M6P, 200 mM or 600 mM) was injected into and around the nerve. After 6 weeks the extent of regeneration was assessed electrophysiologically by determining the ratio of the compound action potential (CAP) modulus evoked by electrical stimulation of the nerve 2 mm distal or proximal to the repair site. The conduction velocity of the fastest components in the CAP was also calculated. The percentage area of collagen staining (PAS) at the repair site was analysed using Picrosirius Red and image analysis. Comparisons were made with a placebo group (100 μl of phosphate buffered saline) and sham-operated controls. The median CAP modulus ratio in the 600 mM M6P group was 0.44, which was significantly higher than in the placebo group (0.24, P=0.012: Kruskal-Wallis test). Conduction velocities were also faster in the 600 mM M6P group (median 30 m s(-1)) than in the placebo group (median 27.8 m s(-1); P=0.0197: Kruskal-Wallis test). None of the other treated groups were significantly different from the placebo, and all had significantly lower CAP ratios than the sham controls (P<0.05). All repair groups had a significantly higher PAS for collagen than sham controls. We conclude that the administration of 600 mM mannose-6-phosphate to a nerve repair site enhances axonal regeneration.
  2. Thomson WM, Foster Page LA, Robinson PG, Do LG, Traebert J, Mohamed AR, et al.
    Community Dent Oral Epidemiol, 2016 12;44(6):549-556.
    PMID: 27477903 DOI: 10.1111/cdoe.12248
    OBJECTIVE: To examine the factor structure and other psychometric characteristics of the most commonly used child oral-health-related quality-of-life (OHRQoL) measure (the 16-item short-form CPQ11-14 ) in a large number of children (N = 5804) from different settings and who had a range of caries experience and associated impacts.

    METHODS: Secondary data analyses used subnational epidemiological samples of 11- to 14-year-olds in Australia (N = 372), New Zealand (three samples: 352, 202, 429), Brunei (423), Cambodia (244), Hong Kong (542), Malaysia (439), Thailand (220, 325), England (88, 374), Germany (1055), Mexico (335) and Brazil (404). Confirmatory factor analysis (CFA) was used to examine the factor structure of the CPQ11-14 across the combined sample and within four regions (Australia/NZ, Asia, UK/Europe and Latin America). Item impact and internal reliability analysis were also conducted.

    RESULTS: Caries experience varied, with mean DMFT scores ranging from 0.5 in the Malaysian sample to 3.4 in one New Zealand sample. Even more variation was noted in the proportion reporting only fair or poor oral health; this was highest in the Cambodian and Mexican samples and lowest in the German sample and one New Zealand sample. One in 10 reported that their oral health had a marked impact on their life overall. The CFA across all samples revealed two factors with eigenvalues greater than 1. The first involved all items in the oral symptoms and functional limitations subscales; the second involved all emotional well-being and social well-being items. The first was designated the 'symptoms/function' subscale, and the second was designated the 'well-being' subscale. Cronbach's alpha scores were 0.72 and 0.84, respectively. The symptoms/function subscale contained more of the items with greater impact, with the item 'Food stuck in between your teeth' having greatest impact; in the well-being subscale, the 'Felt shy or embarrassed' item had the greatest impact. Repeating the analyses by world region gave similar findings.

    CONCLUSION: The CPQ11-14 performed well cross-sectionally in the largest analysis of the scale in the literature to date, with robust and mostly consistent psychometric characteristics, albeit with two underlying factors (rather than the originally hypothesized four-factor structure). It appears to be a sound, robust measure which should be useful for research, practice and policy.

  3. Baker SR, Foster Page L, Thomson WM, Broomhead T, Bekes K, Benson PE, et al.
    J Dent Res, 2018 09;97(10):1129-1136.
    PMID: 29608864 DOI: 10.1177/0022034518767401
    Much research on children's oral health has focused on proximal determinants at the expense of distal (upstream) factors. Yet, such upstream factors-the so-called structural determinants of health-play a crucial role. Children's lives, and in turn their health, are shaped by politics, economic forces, and social and public policies. The aim of this study was to examine the relationship between children's clinical (number of decayed, missing, and filled teeth) and self-reported oral health (oral health-related quality of life) and 4 key structural determinants (governance, macroeconomic policy, public policy, and social policy) as outlined in the World Health Organization's Commission for Social Determinants of Health framework. Secondary data analyses were carried out using subnational epidemiological samples of 8- to 15-y-olds in 11 countries ( N = 6,648): Australia (372), New Zealand (three samples; 352, 202, 429), Brunei (423), Cambodia (423), Hong Kong (542), Malaysia (439), Thailand (261, 506), United Kingdom (88, 374), Germany (1498), Mexico (335), and Brazil (404). The results indicated that the type of political regime, amount of governance (e.g., rule of law, accountability), gross domestic product per capita, employment ratio, income inequality, type of welfare regime, human development index, government expenditure on health, and out-of-pocket (private) health expenditure by citizens were all associated with children's oral health. The structural determinants accounted for between 5% and 21% of the variance in children's oral health quality-of-life scores. These findings bring attention to the upstream or structural determinants as an understudied area but one that could reap huge rewards for public health dentistry research and the oral health inequalities policy agenda.
  4. Hui CY, Condon K, Kolekar S, Roberts N, Sreter KB, Simons SO, et al.
    PLoS One, 2024;19(12):e0314914.
    PMID: 39729438 DOI: 10.1371/journal.pone.0314914
    The value of 'data-enabled', digital healthcare is evolving rapidly, as demonstrated in the COVID-19 pandemic, and its successful implementation remains complex and challenging. Harmonisation (within/between healthcare systems) of infrastructure and implementation strategies has the potential to promote safe, equitable and accessible digital healthcare, but guidance for implementation is lacking. Using respiratory technologies as an example, our scoping review process will capture and review the published research between 12th December 2013 to 12th December 2023. Following standard methodology (Arksey and O'Malley), we will search for studies published in ten databases: MEDLINE, EMBASE, CINAHL, PsycINFO, Cochrane Library, Web of Science, Scopus, IEEE Xplore, CABI Global Health, and WHO Medicus. Our search strategy will use the terms: digital health, respiratory conditions, and implementation. Using Covidence, screening of abstracts and full texts will be undertaken by two independent reviewers, with conflicts resolved by a third reviewer. Data will be extracted into a pilot-tested data extraction table for charting, summarising and reporting the results. We will conduct stakeholder meetings throughout to discuss the themes emerging from implementation studies and support interpretation of findings in the light of their experience within their own networks and organisations. The findings will inform the future work within the ERS CONNECT clinical research collaboration and contribute to policy statements to promote a harmonised framework for digital transformation of respiratory healthcare.
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