Relationships between Oral Health and Nutritional Status of Older Adults

Objectives: The World Health Organisation has highlighted the paucity of research into the oral health needs of older adults. In particular, the relationships between oral health and nutritional status require further investigation and analysis. This study aimed to describe some of the relationships between the number of remaining occluding tooth contacts, oral health related quality of life and nutritional status of partially dentate older adults.

Methods: 45 partially dentate patients aged 65 years and older were recruited to the study after visiting a university dental hospital. An initial dental examination charted the remaining teeth including the number of occluding contacts. Oral health related quality of life was recorded using the 14 item Oral Health Impact Profile. Nutritional status was measured using the Mini Nutritional Assessment (MNA) in addition to biochemical analysis of a haematological sample. Correlation between data values was measured using a Pearson's correlation coefficient (r).

Results: The patient sample was made up of 44% males and 56% females with a mean age of 72.4 years (range 65-84 years). With increasing age the patients' oral health related quality of life scores improved. (r=-0.25) Within the sample the number of occluding tooth contacts ranged from 6 to 11. It was found that as the number of occluding contacts increased, better oral health related quality of life scores were recorded. (r=-0.30) Generally mini nutritional assessment scores improved with increasing numbers of tooth contacts. (r=0.14) In addition, as the number of occluding teeth contacts increased total lymphocyte count (r=0.35), vitamin B12 (r=0.22) and serum folate (r=0.06) all increased.

Conclusions: In older patients increased numbers of tooth contacts are associated with better oral health related quality of life. Increasing numbers of occluding contacts are also associated with better MNA scores and some haematological indicators of nutritional status.

City Profile: Erbil

Erbil (Hawler in Kurdish), is the capital and the largest city of Iraqi Kurdistan. Having been continuously inhabited for about 6000 years, the city has recently been regarded by UNESCO World Heritage as one of the world’s oldest urban settlements. The city is witnessing remarkable urban growth and rapid spatial expansion compounded by a dramatic increase in population due to emigration from the countryside and rural areas over the last three decades. Following the changing geopolitical landscape of post-war Iraq, urban changes and socio-political transformation are largely driven by Erbil’s growing autonomous status as the capital of northern region of Kurdistan since 2003. This paper explores the layers of historical, spatial and social developments of the contemporary urban context of Kurdistan in general and of Erbil in particular as a reflection of the changing status of the city, as well as the polarization of Iraq and the emergence of neoliberal urbanism. The tension between the global and modern from one side and traditional and authentic from another is ever present and evident in everyday challenges in the planning of the city. In large part, Erbil’s built fabric embodies the dichotomy of identity and contests between its past and future, in which the present remains a transition between two disconnected realities.

Slow Release Drug Dissolution Profile Prediction in Pharmaceutical Manufacturing: a Multivariate and Machine Learning Approach

Slow release drugs must be manufactured to meet target specifications with respect to dissolution curve profiles. In this paper we consider the problem of identifying the drivers of dissolution curve variability of a drug from historical manufacturing data. Several data sources are considered: raw material parameters, coating data, loss on drying and pellet size statistics. The methodology employed is to develop predictive models using LASSO, a powerful machine learning algorithm for regression with high-dimensional datasets. LASSO provides sparse solutions facilitating the identification of the most important causes of variability in the drug fabrication process. The proposed methodology is illustrated using manufacturing data for a slow release drug.

Dynamic modelling of die melt temperature profile in polymer extrusion: Effects of process settings, screw geometry and material

Extrusion is one of the major methods for processing polymeric materials and the thermal homogeneity of the process output is a major concern for manufacture of high quality extruded products. Therefore, accurate process thermal monitoring and control are important for product quality control. However, most industrial extruders use single point thermocouples for the temperature monitoring/control although their measurements are highly affected by the barrel metal wall temperature. Currently, no industrially established thermal profile measurement technique is available. Furthermore, it has been shown that the melt temperature changes considerably with the die radial position and hence point/bulk measurements are not sufficient for monitoring and control of the temperature across the melt flow. The majority of process thermal control methods are based on linear models which are not capable of dealing with process nonlinearities. In this work, the die melt temperature profile of a single screw extruder was monitored by a thermocouple mesh technique. The data obtained was used to develop a novel approach of modelling the extruder die melt temperature profile under dynamic conditions (i.e. for predicting the die melt temperature profile in real-time). These newly proposed models were in good agreement with the measured unseen data. They were then used to explore the effects of process settings, material and screw geometry on the die melt temperature profile. The results showed that the process thermal homogeneity was affected in a complex manner by changing the process settings, screw geometry and material.

Mycosis fungoides shows concurrent deregulation of multiple genes involved in the TNF signaling pathway:an expression profile study

Mycosis fungoides (MF) is the most frequent type of cutaneous T-cell lymphoma, whose diagnosis and study is hampered by its morphologic similarity to inflammatory dermatoses (ID) and the low proportion of tumoral cells, which often account for only 5% to 10% of the total tissue cells. cDNA microarray studies using the CNIO OncoChip of 29 MF and 11 ID cases revealed a signature of 27 genes implicated in the tumorigenesis of MF, including tumor necrosis factor receptor (TNFR)-dependent apoptosis regulators, STAT4, CD40L, and other oncogenes and apoptosis inhibitors. Subsequently a 6-gene prediction model was constructed that is capable of distinguishing MF and ID cases with unprecedented accuracy. This model correctly predicted the class of 97% of cases in a blind test validation using 24 MF patients with low clinical stages. Unsupervised hierarchic clustering has revealed 2 major subclasses of MF, one of which tends to include more aggressive-type MF cases including tumoral MF forms. Furthermore, signatures associated with abnormal immunophenotype (11 genes) and tumor stage disease (5 genes) were identified.

Whole genome protein microarrays for serum profiling of immunodominant antigens of Bacillus anthracis

A commercial Bacillus anthracis (Anthrax) whole genome protein microarray has been used to identify immunogenic Anthrax proteins (IAP) using sera from groups of donors with (a) confirmed B. anthracis naturally acquired cutaneous infection, (b) confirmed B. anthracis intravenous drug use-acquired infection, (c) occupational exposure in a wool-sorters factory, (d) humans and rabbits vaccinated with the UK Anthrax protein vaccine and compared to naïve unexposed controls. Anti-IAP responses were observed for both IgG and IgA in the challenged groups; however the anti-IAP IgG response was more evident in the vaccinated group and the anti-IAP IgA response more evident in the B. anthracis-infected groups. Infected individuals appeared somewhat suppressed for their general IgG response, compared with other challenged groups. Immunogenic protein antigens were identified in all groups, some of which were shared between groups whilst others were specific for individual groups. The toxin proteins were immunodominant in all vaccinated, infected or other challenged groups. However, a number of other chromosomally-located and plasmid encoded open reading frame proteins were also recognized by infected or exposed groups in comparison to controls. Some of these antigens e.g., BA4182 are not recognized by vaccinated individuals, suggesting that there are proteins more specifically expressed by live Anthrax spores in vivo that are not currently found in the UK licensed Anthrax Vaccine (AVP). These may perhaps be preferentially expressed during infection and represent expression of alternative pathways in the B. anthracis "infectome." These may make highly attractive candidates for diagnostic and vaccine biomarker development as they may be more specifically associated with the infectious phase of the pathogen. A number of B. anthracis small hypothetical protein targets have been synthesized, tested in mouse immunogenicity studies and validated in parallel using human sera from the same study.

Dynamic axle force and road profile identification using a moving vehicle

The axle forces applied by a vehicle through its wheels are a critical part of the interaction between vehicles, pavements and bridges. Therefore, the minimisation of these forces is important in order to promote long pavement life spans and ensure that bridge loads are small. Moreover, as the road surface roughness affects the vehicle dynamic forces, the monitoring of pavements for highways and bridges is an important task. This paper presents a novel algorithm to identify these dynamic interaction forces which involves direct instrumentation of a vehicle with accelerometers. The ability of this approach to predict the pavement roughness is also presented. Moving force identification theory is applied to a vehicle model in theoretical simulations in order to obtain the interaction forces and pavement roughness from the measured accelerations. The method is tested for a range of bridge spans in simulations and the influence of road roughness level on the accuracy of the results is investigated. Finally, the challenge for the real-world problem is addressed in a laboratory experiment.

Predicting conversion to dementia in a memory clinic: A standard clinical approach compared with an empirically defined clustering method (latent profile analysis) for mild cognitive impairment subtyping

Introduction
Mild cognitive impairment (MCI) has clinical value in its ability to predict later dementia. A better understanding of cognitive profiles can further help delineate who is most at risk of conversion to dementia. We aimed to (1) examine to what extent the usual MCI subtyping using core criteria corresponds to empirically defined clusters of patients (latent profile analysis [LPA] of continuous neuropsychological data) and (2) compare the two methods of subtyping memory clinic participants in their prediction of conversion to dementia.

Methods
Memory clinic participants (MCI, n = 139) and age-matched controls (n = 98) were recruited. Participants had a full cognitive assessment, and results were grouped (1) according to traditional MCI subtypes and (2) using LPA. MCI participants were followed over approximately 2 years after their initial assessment to monitor for conversion to dementia.

Results
Groups were well matched for age and education. Controls performed significantly better than MCI participants on all cognitive measures. With the traditional analysis, most MCI participants were in the amnestic multidomain subgroup (46.8%) and this group was most at risk of conversion to dementia (63%). From the LPA, a three-profile solution fit the data best. Profile 3 was the largest group (40.3%), the most cognitively impaired, and most at risk of conversion to dementia (68% of the group).

Discussion
LPA provides a useful adjunct in delineating MCI participants most at risk of conversion to dementia and adds confidence to standard categories of clinical inference.

Serum- and HDL3-serum amyloid A and HDL3-LCAT activity are influenced by increased CVD-burden

BACKGROUND: High density lipoproteins (HDL) protect against cardiovascular disease (CVD). However, increased serum amyloid-A (SAA) related inflammation may negate this property. This study investigated if SAA was related to CVD-burden.

METHODS: Subjects referred to the rapid chest pain clinic (n = 240) had atherosclerotic burden assessed by cardiac computerised tomography angiography. Subjects were classified as: no-CVD (n = 106), non-obstructive-CVD, stenosis<50% (n = 58) or moderate/significant-CVD, stenosis ≥50% (n = 76). HDL was subfractionated into HDL2 and HDL3 by rapid-ultracentrifugation. SAA-concentration was measured by ELISA and lecithin cholesterol acyltransferase (LCAT) activity measured by a fluorimetric assay.

RESULTS: We illustrated that serum-SAA and HDL3-SAA-concentration were higher and HDL3-LCAT-activity lower in the moderate/significant-CVD-group, compared to the no-CVD and non-obstructive-CVD-groups (percent differences: serum-SAA, +33% & +30%: HDL3-SAA, +65% and +39%: HDL3-LCAT, -6% & -3%; p < 0.05 for all comparisons). We also identified a positive correlation between serum-SAA and HDL3-SAA (r = 0.698; p < 0.001) and a negative correlation between HDL3-SAA and HDL3-LCAT-activity (r = -0.295; p = 0.003), while CVD-burden positively correlated with serum-SAA (r = 0.150; p < 0.05) and HDL3-SAA (r = 0.252; p < 0.001) and negatively correlated with HDL3-LCAT-activity (r = -0.182; p = 0.006). Additionally, multivariate regression analysis adjusted for age, gender, CRP and serum-SAA illustrated that HDL3-SAA was significantly associated with modifying CVD-risk of moderate/significant CVD-risk (p < 0.05).

CONCLUSION: This study has demonstrated increased SAA-related inflammation in subjects with moderate/significant CVD-burden, which appeared to impact on the antiatherogenic potential of HDL. We suggest that SAA may be a useful biomarker to illustrate increased CVD-burden, although this requires further investigation.

Serum Cytokines and Adipokines in Periodontitis

Objective: To investigate whether there was an association between serum levels of pro-inflammatory cytokines, adipokines and periodontitis in 60-70 year-old men in Northern Ireland. Methods: Test subjects (n=61) with established periodontitis, categorised by loss of periodontal attachment (PAL) and pocketing of at least 5mm, were matched for age, smoking and BMI with controls (n=60) who were periodontitis resistant (no PAL or pocketing over 3mm). Serum levels of IL 1 alpha, TNF alpha, IL 6, adiponectin, resistin, leptin and C-reactive protein (CRP) were measured from serum using a multiplex array (Randox, UK). Mann Whitney analysis was used with the level of significance set at p<0.05. Results: There was considerable inter-individual variability in all the analytes measured. There was a significantly higher level of IL 6 in men with periodontitis (3.25 pg/ml, SD 2.29) than in those with no periodontitis (2.38 pg/ml, SD1.62), p=0.0041 (after Bonferroni correction for multiple testing p=0.029). Serum IL 6 was strongly correlated with CRP: r=0.52 (95% CI 0.38-0.64), p<0.0001. There was a lower serum level of adiponectin in men with periodontitis (3662.1 ng/ml, SD 2383.4) compared with those who were periodontitis resistant (4265.9 ng/ml, SD 2266.0), which just escaped statistical significance at p=0.068. There were no significant differences in the serum levels of any of the other analytes measured in relation to periodontal status. Conclusions: There was evidence in the 60-70 year-old male population investigated that periodontitis was associated with an increased serum level of IL 6.

Microbiological Profile of Aggressive Periodontitis in a Sudanese Population

Background: Several bacterial species have been identified as being associated with aggressive periodontitis (AgP) notably Aggregatibacter actinomycetemcomitans (Aa) and Porphyromonas gingivalis (Pg). There are limited data on bacterial associations with AgP in African populations. Objective: To investigate possible associations between specific bacteria and AgP in a Sudanese population. Methods: Subgingival plaque samples were collected from 93 (20 male, 73 female) Sudanese patients diagnosed with AgP and from 72 (23 male, 48 female) periodontally healthy Sudanese controls. Quantitative PCR was used to identify Aa, Pg, Treponema denticola (Td) and Fusobacterium nucleatum (Fn). The prevalence of these bacterial species was compared using Chi-square analysis. Odds ratios (OR) were calculated using standard methods. Results: The cases with AgP were well matched in age with the controls: 24.8 (SD 5.1) compared with 23.5 (SD 3.7) years, p=0.07. There was a significantly higher prevalence of Pg in AgP (73%) than in the controls (33%), p<0.0001. The OR for Pg to be associated with AgP was 5.44 (95% confidence intervals 2.78-10.64). In 26 (38%) of the AgP cases positive for Pg there were low levels of this bacterium (<100 copies). Both Td and Fn were identified in virtually all (>95%) the plaque samples studied from both AgP and controls. Aa was the least frequently identified species and was present in only 28% of AgP and 18% of controls, p=0.14. The OR for Aa to be associated with AgP was slightly increased at 1.76 (95% CI 0.83-3.74), however, this was not significant (p=0.14). Conclusion: In the Sudanese subjects studied Pg but not Aa was associated with AgP. There were very low levels of Pg in many of the plaque samples from AgP.