Assessing the Oral Health Needs of Public Housing Residents

Objectives: “Tooth Smart Healthy Start” is a randomized clinical trial which aims to reduce the incidence of early childhood caries (ECC) in Boston public housing residents as part of the NIH funded Northeast Center for Research to Evaluate and Eliminate Dental Disparities. The purpose of this project was to assess public housing stakeholders' perception of the oral health needs of public housing residents and their interest in replicating “Tooth Smart Healthy Start” in other public housing sites across the nation. Methods: The target population was the 180 attendees of the 2010 meeting of the Health Care for Residents of Public Housing National Conference. A ten question survey which assessed conference attendees' beliefs about oral health and its importance to public housing residents was distributed. Data was analyzed using SAS 9.1. Descriptive statistics were calculated for each variable and results were stratified by participants' roles. Results: Thirty percent of conference attendees completed the survey. The participants consisted of residents, agency representatives, and housing authority personnel. When asked to rank health issues facing public housing residents, oral health was rated as most important (42%) or top three (16%) by residents. The agency representatives and housing authority personnel rated oral health among the top three (33% and 58% respectively) and top five (36% and 25% respectively). When participants ranked the three greatest resident health needs out of eight choices, oral health was the most common response. Majority of the participants expressed interest in replicating the “Tooth Smart Healthy Start” program at their sites. Conclusion: All stakeholder groups identified oral health as one of the greatest health needs of residents in public housing. Furthermore, if shown to reduce ECC, there is significant interest in implementing the program amongst key public housing stakeholders across the nation.

Uncertainty in wind energy forecasting

Wind energy is the energy source that contributes most to the renewable energy mix of European countries. While there are good wind resources throughout Europe, the intermittency of the wind represents a major problem for the deployment of wind energy into the electricity networks. To ensure grid security a Transmission System Operator needs today for each kilowatt of wind energy either an equal amount of spinning reserve or a forecasting system that can predict the amount of energy that will be produced from wind over a period of 1 to 48 hours. In the range from 5m/s to 15m/s a wind turbine’s production increases with a power of three. For this reason, a Transmission System Operator requires an accuracy for wind speed forecasts of 1m/s in this wind speed range. Forecasting wind energy with a numerical weather prediction model in this context builds the background of this work. The author’s goal was to present a pragmatic solution to this specific problem in the ”real world”. This work therefore has to be seen in a technical context and hence does not provide nor intends to provide a general overview of the benefits and drawbacks of wind energy as a renewable energy source. In the first part of this work the accuracy requirements of the energy sector for wind speed predictions from numerical weather prediction models are described and analysed. A unique set of numerical experiments has been carried out in collaboration with the Danish Meteorological Institute to investigate the forecast quality of an operational numerical weather prediction model for this purpose. The results of this investigation revealed that the accuracy requirements for wind speed and wind power forecasts from today’s numerical weather prediction models can only be met at certain times. This means that the uncertainty of the forecast quality becomes a parameter that is as important as the wind speed and wind power itself. To quantify the uncertainty of a forecast valid for tomorrow requires an ensemble of forecasts. In the second part of this work such an ensemble of forecasts was designed and verified for its ability to quantify the forecast error. This was accomplished by correlating the measured error and the forecasted uncertainty on area integrated wind speed and wind power in Denmark and Ireland. A correlation of 93% was achieved in these areas. This method cannot solve the accuracy requirements of the energy sector. By knowing the uncertainty of the forecasts, the focus can however be put on the accuracy requirements at times when it is possible to accurately predict the weather. Thus, this result presents a major step forward in making wind energy a compatible energy source in the future.

The differences in the social competence of children who attend integrated junior infant classes and children who attend segregated learning environments

There are a number of reasons why this researcher has decided to undertake this study into the differences in the social competence of children who attend integrated Junior Infant classes and children who attend segregated learning environments. Theses reasons are both personal and professional. My personal reasons stem from having grown up in a family which included both an aunt who presented with Down Syndrome and an uncle who presented with hearing impairment. Both of these relatives' experiences in our education system are interesting. My aunt was considered ineducable while her brother - my uncle - was sent to Dublin (from Cork) at six years of age to be educated by a religious order. My professional reasons, on the other hand, stemmed from my teaching experience. Having taught in both special and integrated classrooms it became evident to me that there was somewhat 'suspicion' attached to integration. Parents of children without disabilities questioned whether this process would have a negative impact on their children's education. While parents of children with disabilities debated whether integrated settings met the specific needs of their children. On the other hand, I always questioned whether integration and inclusiveness meant the same thing. My research has enabled me to find many answers. Increasingly, children with special educational needs (SEN) are attending a variety of integrated and inclusive childcare and education settings. This contemporary practice of educating children who present with disabilities in mainstream classrooms has stimulated vast interest on the impact of such practices on children with identified disabilities. Indeed, children who present with disabilities "fare far better in mainstream education than in special schools" (Buckley, cited in Siggins, 2001,p.25). However, educators and practitioners in the field of early years education and care are concerned with meeting the needs of all children in their learning environments, while also upholding high academic standards (Putman, 1993). Fundamentally, therefore, integrated education must also produce questions about the impact of this practice on children without identified special educational needs. While these questions can be addressed from the various areas of child development (i.e. cognitive, physical, linguistic, emotional, moral, spiritual and creative), this research focused on the social domain. It investigates the development of social competence in junior infant class children without identified disabilities as they experience different educational settings.

Dairy-Met: compositional metagenomic analysis of milk and cheeses

Unpasteurised milk and many cheeses contain a diverse microbiological population. These microorganisms play important roles in dairy foods and can, for example, contribute to the development of flavours and aromas, determine safety, cause spoilage or enhance the health of the consumer. It is thus important to understand thoroughly the microorganisms present in these food types. Traditional culture dependent and culture-independent methods have provided much detail regarding the microbial content of dairy foods. However, the development of next-generation DNA sequencing technologies has revolutionised our knowledge of complex microbial environments. Throughout this thesis we observe the benefits of applying these technologies to provide a detailed understanding of the bacterial content of dairy foods, including those present in milk pre- and post-pasteurisation, Irish farmhouse cheeses and commercially produced cheeses which encounter a discolouration defect, as well as to study genomic changes in microbes associated with dairy foods. Through the application of these state-of-the-art technologies we identified the presence of microorganisms not previously associated with dairy foods.

Caregivers of people with neurodegenerative diseases: profile and unmet needs from a population-based survey in South Australia.

INTRODUCTION: Neurodegenerative diseases (NDD) are characterized by progressive decline and loss of function, requiring considerable third-party care. NDD carers report low quality of life and high caregiver burden. Despite this, little information is available about the unmet needs of NDD caregivers. METHODS: Data from a cross-sectional, whole of population study conducted in South Australia were analyzed to determine the profile and unmet care needs of people who identify as having provided care for a person who died an expected death from NDDs including motor neurone disease and multiple sclerosis. Bivariate analyses using chi(2) were complemented with a regression analysis. RESULTS: Two hundred and thirty respondents had a person close to them die from an NDD in the 5 years before responding. NDD caregivers were more likely to have provided care for more than 2 years and were more able to move on after the death than caregivers of people with other disorders such as cancer. The NDD caregivers accessed palliative care services at the same rate as other caregivers at the end of life, however people with an NDD were almost twice as likely to die in the community (odds ratio [OR] 1.97; 95% confidence interval [CI] 1.30 to 3.01) controlling for relevant caregiver factors. NDD caregivers reported significantly more unmet needs in emotional, spiritual, and bereavement support. CONCLUSION: This study is the first step in better understanding across the whole population the consequences of an expected death from an NDD. Assessments need to occur while in the role of caregiver and in the subsequent bereavement phase.

Coordination of platinum therapeutic agents to met-rich motifs of human copper transport protein1.

Platinum therapeutic agents are widely used in the treatment of several forms of cancer. Various mechanisms for the transport of the drugs have been proposed including passive diffusion across the cellular membrane and active transport via proteins. The copper transport protein Ctr1 is responsible for high affinity copper uptake but has also been implicated in the transport of cisplatin into cells. Human hCtr1 contains two methionine-rich Mets motifs on its extracellular N-terminus that are potential platinum-binding sites: the first one encompasses residues 7-14 with amino acid sequence Met-Gly-Met-Ser-Tyr-Met-Asp-Ser and the second one spans residues 39-46 with sequence Met-Met-Met-Met-Pro-Met-Thr-Phe. In these studies, we use liquid chromatography and mass spectrometry to compare the binding interactions between cisplatin, carboplatin and oxaliplatin with synthetic peptides corresponding to hCtr1 Mets motifs. The interactions of cisplatin and carboplatin with Met-rich motifs that contain three or more methionines result in removal of the carrier ligands of both platinum complexes. In contrast, oxaliplatin retains its cyclohexyldiamine ligand upon platinum coordination to the peptide.

Child work and labour among orphaned and abandoned children in five low and middle income countries.

BACKGROUND: The care and protection of the estimated 143,000,000 orphaned and abandoned children (OAC) worldwide is of great importance to global policy makers and child service providers in low and middle income countries (LMICs), yet little is known about rates of child labour among OAC, what child and caregiver characteristics predict child engagement in work and labour, or when such work infers with schooling. This study examines rates and correlates of child labour among OAC and associations of child labour with schooling in a cohort of OAC in 5 LMICs. METHODS: The Positive Outcomes for Orphans (POFO) study employed a two-stage random sampling survey methodology to identify 1480 single and double orphans and children abandoned by both parents ages 6-12 living in family settings in five LMICs: Cambodia, Ethiopia, India, Kenya, and Tanzania. Regression models examined child and caregiver associations with: any work versus no work; and with working <21, 21-27, and 28+ hours during the past week, and child labour (UNICEF definition). RESULTS: The majority of OAC (60.7%) engaged in work during the past week, and of those who worked, 17.8% (10.5% of the total sample) worked 28 or more hours. More than one-fifth (21.9%; 13% of the total sample) met UNICEF's child labour definition. Female OAC and those in good health had increased odds of working. OAC living in rural areas, lower household wealth and caregivers not earning an income were associated with increased child labour. Child labour, but not working fewer than 28 hours per week, was associated with decreased school attendance. CONCLUSIONS: One in seven OAC in this study were reported to be engaged in child labour. Policy makers and social service providers need to pay close attention to the demands being placed on female OAC, particularly in rural areas and poor households with limited income sources. Programs to promote OAC school attendance may need to focus on the needs of families as well as the OAC.

Crossing the cultural divide: assessing the needs of a local immigrant community

Gemstone Team CARE (Community Assessment of Resident Experiences)

Specializing pedestrian maps to address the needs of people using wheelchairs: a case study in community-sustainable information systems

Gemstone Team FASTR (Finding Alternative Specialized Travel Routes)

Micro-Anatomical Quantitative Imaging Towards Enabling Automated Diagnosis of Thick Tissues at the Point of Care

Histopathology is the clinical standard for tissue diagnosis. However, histopathology has several limitations including that it requires tissue processing, which can take 30 minutes or more, and requires a highly trained pathologist to diagnose the tissue. Additionally, the diagnosis is qualitative, and the lack of quantitation leads to possible observer-specific diagnosis. Taken together, it is difficult to diagnose tissue at the point of care using histopathology.

Several clinical situations could benefit from more rapid and automated histological processing, which could reduce the time and the number of steps required between obtaining a fresh tissue specimen and rendering a diagnosis. For example, there is need for rapid detection of residual cancer on the surface of tumor resection specimens during excisional surgeries, which is known as intraoperative tumor margin assessment. Additionally, rapid assessment of biopsy specimens at the point-of-care could enable clinicians to confirm that a suspicious lesion is successfully sampled, thus preventing an unnecessary repeat biopsy procedure. Rapid and low cost histological processing could also be potentially useful in settings lacking the human resources and equipment necessary to perform standard histologic assessment. Lastly, automated interpretation of tissue samples could potentially reduce inter-observer error, particularly in the diagnosis of borderline lesions.

To address these needs, high quality microscopic images of the tissue must be obtained in rapid timeframes, in order for a pathologic assessment to be useful for guiding the intervention. Optical microscopy is a powerful technique to obtain high-resolution images of tissue morphology in real-time at the point of care, without the need for tissue processing. In particular, a number of groups have combined fluorescence microscopy with vital fluorescent stains to visualize micro-anatomical features of thick (i.e. unsectioned or unprocessed) tissue. However, robust methods for segmentation and quantitative analysis of heterogeneous images are essential to enable automated diagnosis. Thus, the goal of this work was to obtain high resolution imaging of tissue morphology through employing fluorescence microscopy and vital fluorescent stains and to develop a quantitative strategy to segment and quantify tissue features in heterogeneous images, such as nuclei and the surrounding stroma, which will enable automated diagnosis of thick tissues.

To achieve these goals, three specific aims were proposed. The first aim was to develop an image processing method that can differentiate nuclei from background tissue heterogeneity and enable automated diagnosis of thick tissue at the point of care. A computational technique called sparse component analysis (SCA) was adapted to isolate features of interest, such as nuclei, from the background. SCA has been used previously in the image processing community for image compression, enhancement, and restoration, but has never been applied to separate distinct tissue types in a heterogeneous image. In combination with a high resolution fluorescence microendoscope (HRME) and a contrast agent acriflavine, the utility of this technique was demonstrated through imaging preclinical sarcoma tumor margins. Acriflavine localizes to the nuclei of cells where it reversibly associates with RNA and DNA. Additionally, acriflavine shows some affinity for collagen and muscle. SCA was adapted to isolate acriflavine positive features or APFs (which correspond to RNA and DNA) from background tissue heterogeneity. The circle transform (CT) was applied to the SCA output to quantify the size and density of overlapping APFs. The sensitivity of the SCA+CT approach to variations in APF size, density and background heterogeneity was demonstrated through simulations. Specifically, SCA+CT achieved the lowest errors for higher contrast ratios and larger APF sizes. When applied to tissue images of excised sarcoma margins, SCA+CT correctly isolated APFs and showed consistently increased density in tumor and tumor + muscle images compared to images containing muscle. Next, variables were quantified from images of resected primary sarcomas and used to optimize a multivariate model. The sensitivity and specificity for differentiating positive from negative ex vivo resected tumor margins was 82% and 75%. The utility of this approach was further tested by imaging the in vivo tumor cavities from 34 mice after resection of a sarcoma with local recurrence as a bench mark. When applied prospectively to images from the tumor cavity, the sensitivity and specificity for differentiating local recurrence was 78% and 82%. The results indicate that SCA+CT can accurately delineate APFs in heterogeneous tissue, which is essential to enable automated and rapid surveillance of tissue pathology.

Two primary challenges were identified in the work in aim 1. First, while SCA can be used to isolate features, such as APFs, from heterogeneous images, its performance is limited by the contrast between APFs and the background. Second, while it is feasible to create mosaics by scanning a sarcoma tumor bed in a mouse, which is on the order of 3-7 mm in any one dimension, it is not feasible to evaluate an entire human surgical margin. Thus, improvements to the microscopic imaging system were made to (1) improve image contrast through rejecting out-of-focus background fluorescence and to (2) increase the field of view (FOV) while maintaining the sub-cellular resolution needed for delineation of nuclei. To address these challenges, a technique called structured illumination microscopy (SIM) was employed in which the entire FOV is illuminated with a defined spatial pattern rather than scanning a focal spot, such as in confocal microscopy.

Thus, the second aim was to improve image contrast and increase the FOV through employing wide-field, non-contact structured illumination microscopy and optimize the segmentation algorithm for new imaging modality. Both image contrast and FOV were increased through the development of a wide-field fluorescence SIM system. Clear improvement in image contrast was seen in structured illumination images compared to uniform illumination images. Additionally, the FOV is over 13X larger than the fluorescence microendoscope used in aim 1. Initial segmentation results of SIM images revealed that SCA is unable to segment large numbers of APFs in the tumor images. Because the FOV of the SIM system is over 13X larger than the FOV of the fluorescence microendoscope, dense collections of APFs commonly seen in tumor images could no longer be sparsely represented, and the fundamental sparsity assumption associated with SCA was no longer met. Thus, an algorithm called maximally stable extremal regions (MSER) was investigated as an alternative approach for APF segmentation in SIM images. MSER was able to accurately segment large numbers of APFs in SIM images of tumor tissue. In addition to optimizing MSER for SIM image segmentation, an optimal frequency of the illumination pattern used in SIM was carefully selected because the image signal to noise ratio (SNR) is dependent on the grid frequency. A grid frequency of 31.7 mm-1 led to the highest SNR and lowest percent error associated with MSER segmentation.

Once MSER was optimized for SIM image segmentation and the optimal grid frequency was selected, a quantitative model was developed to diagnose mouse sarcoma tumor margins that were imaged ex vivo with SIM. Tumor margins were stained with acridine orange (AO) in aim 2 because AO was found to stain the sarcoma tissue more brightly than acriflavine. Both acriflavine and AO are intravital dyes, which have been shown to stain nuclei, skeletal muscle, and collagenous stroma. A tissue-type classification model was developed to differentiate localized regions (75x75 µm) of tumor from skeletal muscle and adipose tissue based on the MSER segmentation output. Specifically, a logistic regression model was used to classify each localized region. The logistic regression model yielded an output in terms of probability (0-100%) that tumor was located within each 75x75 µm region. The model performance was tested using a receiver operator characteristic (ROC) curve analysis that revealed 77% sensitivity and 81% specificity. For margin classification, the whole margin image was divided into localized regions and this tissue-type classification model was applied. In a subset of 6 margins (3 negative, 3 positive), it was shown that with a tumor probability threshold of 50%, 8% of all regions from negative margins exceeded this threshold, while over 17% of all regions exceeded the threshold in the positive margins. Thus, 8% of regions in negative margins were considered false positives. These false positive regions are likely due to the high density of APFs present in normal tissues, which clearly demonstrates a challenge in implementing this automatic algorithm based on AO staining alone.

Thus, the third aim was to improve the specificity of the diagnostic model through leveraging other sources of contrast. Modifications were made to the SIM system to enable fluorescence imaging at a variety of wavelengths. Specifically, the SIM system was modified to enabling imaging of red fluorescent protein (RFP) expressing sarcomas, which were used to delineate the location of tumor cells within each image. Initial analysis of AO stained panels confirmed that there was room for improvement in tumor detection, particularly in regards to false positive regions that were negative for RFP. One approach for improving the specificity of the diagnostic model was to investigate using a fluorophore that was more specific to staining tumor. Specifically, tetracycline was selected because it appeared to specifically stain freshly excised tumor tissue in a matter of minutes, and was non-toxic and stable in solution. Results indicated that tetracycline staining has promise for increasing the specificity of tumor detection in SIM images of a preclinical sarcoma model and further investigation is warranted.

In conclusion, this work presents the development of a combination of tools that is capable of automated segmentation and quantification of micro-anatomical images of thick tissue. When compared to the fluorescence microendoscope, wide-field multispectral fluorescence SIM imaging provided improved image contrast, a larger FOV with comparable resolution, and the ability to image a variety of fluorophores. MSER was an appropriate and rapid approach to segment dense collections of APFs from wide-field SIM images. Variables that reflect the morphology of the tissue, such as the density, size, and shape of nuclei and nucleoli, can be used to automatically diagnose SIM images. The clinical utility of SIM imaging and MSER segmentation to detect microscopic residual disease has been demonstrated by imaging excised preclinical sarcoma margins. Ultimately, this work demonstrates that fluorescence imaging of tissue micro-anatomy combined with a specialized algorithm for delineation and quantification of features is a means for rapid, non-destructive and automated detection of microscopic disease, which could improve cancer management in a variety of clinical scenarios.

Development of a Novel c-MET-Based CTC Detection Platform.

UNLABELLED: Amplification of the MET oncogene is associated with poor prognosis, metastatic dissemination, and drug resistance in many malignancies. We developed a method to capture and characterize circulating tumor cells (CTC) expressing c-MET using a ferromagnetic antibody. Immunofluorescence was used to characterize cells for c-MET, DAPI, and pan-CK, excluding CD45(+) leukocytes. The assay was validated using appropriate cell line controls spiked into peripheral blood collected from healthy volunteers (HV). In addition, peripheral blood was analyzed from patients with metastatic gastric, pancreatic, colorectal, bladder, renal, or prostate cancers. CTCs captured by c-MET were enumerated, and DNA FISH for MET amplification was performed. The approach was highly sensitive (80%) for MET-amplified cells, sensitive (40%-80%) for c-MET-overexpressed cells, and specific (100%) for both c-MET-negative cells and in 20 HVs. Of 52 patients with metastatic carcinomas tested, c-MET CTCs were captured in replicate samples from 3 patients [gastric, colorectal, and renal cell carcinoma (RCC)] with 6% prevalence. CTC FISH demonstrated that MET amplification in both gastric and colorectal cancer patients and trisomy 7 with gain of MET gene copies in the RCC patient. The c-MET CTC assay is a rapid, noninvasive, sensitive, and specific method for detecting MET-amplified tumor cells. CTCs with MET amplification can be detected in patients with gastric, colorectal, and renal cancers. IMPLICATIONS: This study developed a novel c-MET CTC assay for detecting c-MET CTCs in patients with MET amplification and warrants further investigation to determine its clinical applicability. Mol Cancer Res; 14(6); 539-47. ©2016 AACR.

Aspects of care 5: the continuing educational needs of midwives

This is the fifth in a series of six papers presenting key findings from a national study that was undertaken to investigate the role and responsibilities of midwives and to identify continuing educational need. The background to the study and the titles of the other papers in the series have been outlined in the first paper. This paper focuses on the methods used to identify the continuing educational needs of midwives, and provides an overview of the findings related to midwives' perceived confidence/competence to practice and their continuing educational needs.

Aspects of care 6: continuing educational needs of midwives 2

This is the last in a series of six papers presenting key findings from a national study that was undertaken to investigate the role and responsibilities of midwives in England and to identify and address continuing educational needs. The background to the study and the titles of other papers in the series have been outlined in the first paper. The first five papers have provided an overview of the main research findings that have been used to determine the continuing educational needs of midwives. This paper provides a more detailed picture of the issues that were identified in relation to educational need, and an overview of the way in which an educational package was developed on the basis of the research findings for use by midwives nationally.

Staff training in the mental health needs of people with learning disabilities in the UK

This paper gives a general overview of some of the factors involved in the training and knowledge of learning disabilities staff relating to mental health. Early indications from research have shown that training may be effective as a way of addressing these problems, but further research and clear guidance on best practice in implementing staff training are needed in this important area.

Vibrational spectra and crystal structure of the di-amino acid peptide cyclo(L-Met-L-Met): Comparison of experimental data and DFT calculations

Experimental Raman and FT-IR spectra of solid-state non-deuterated and N-deuterated samples of cyclo(L-Met-L-Met) are reported and discussed. The Raman and FT-IR results show characteristic amide I vibrations (Raman: 1649 cm-1, infrared: 1675 cm-1) for molecules exhibiting a cis amide conformation. A Raman band, assigned to the cis amide II vibrational mode, is observed at sim1493 cm-1 but no IR band is observed in this region. Cyclo(L-Met-L-Met) crystallises in the triclinic space group P1 with one molecule per unit cell. The overall shape of the diketopiperazine (DKP) ring displays a (slightly distorted) boat conformation. The crystal packing employs two strong hydrogen bonds, which traverse the entire crystal via translational repeats. B3-LYP/cc-pVDZ calculations of the structure of the molecule predict a boat conformation for the DKP ring, in agreement with the experimentally determined X-ray structure. Copyright © 2009 John Wiley & Sons, Ltd.