Effectiveness of a new toothbrush design versus a conventional tongue scraper in improving breath odor and reducing tongue microbiota

For centuries, specific instruments or regular toothbrushes have routinely been used to remove tongue biofilm and improve breath odor. Toothbrushes with a tongue scraper on the back of their head have recently been introduced to the market. The present study compared the effectiveness of a manual toothbrush with this new design, i.e., possessing a tongue scraper, and a commercial tongue scraper in improving breath odor and reducing the aerobic and anaerobic microbiota of tongue surface. The evaluations occurred at 4 moments, when the participants (n=30) had their halitosis quantified with a halimeter and scored according to a 4-point scoring system corresponding to different levels of intensity. Saliva was collected for counts of aerobic and anaerobic microorganisms. Data were analyzed statistically by Friedman's test (p<0.05). When differences were detected, the Wilcoxon test adjusted for Bonferroni correction was used for multiple comparisons (group to group). The results confirmed the importance of mechanical cleaning of the tongue, since this procedure provided an improvement in halitosis and reduction of aerobe and anaerobe counts. Regarding the evaluated methods, the toothbrush's tongue scraper and conventional tongue scraper had a similar performance in terms of breath improvement and reduction of tongue microbiota, and may be indicated as effective methods for tongue cleaning.

Electrocatalytic oxidation of methanol by the [Ru3O(OAc)6(py)2(CH3OH)]3+cluster: improving the metal-ligand electron transfer by accessing the higher oxidation states of a multicentered system

The [Ru3O(Ac)6(py)2(CH3OH)]+ cluster provides an effective electrocatalytic species for the oxidation of methanol under mild conditions. This complex exhibits characteristic electrochemical waves at -1.02, 0.15 and 1.18 V, associated with the Ru3III,II,II/Ru3III,III,II/Ru 3III,III,III /Ru3IV,III,III successive redox couples, respectively. Above 1.7 V, formation of two RuIV centers enhances the 2-electron oxidation of the methanol ligand yielding formaldehyde, in agreement with the theoretical evolution of the HOMO levels as a function of the oxidation states. This work illustrates an important strategy to improve the efficiency of the oxidation catalysis, by using a multicentered redox catalyst and accessing its multiple higher oxidation states.

Do school based food and nutrition policies improve diet and reduce obesity?

OBJECTIVE: To review the effectiveness of school food and nutrition policies world wide in improving the school food environment, student's dietary intake, and decreasing overweight and obesity. METHODS: Systematic review of published and unpublished literature up to November 2007 of three categories of nutrition policy; nutrition guidelines, regulation of food and/or beverage availability, and price interventions applied in preschools, primary and secondary schools. RESULTS: 18 studies met the inclusion criteria. Most evidence of effectiveness was found for the impact of both nutrition guidelines and price interventions on intake and availability of food and drinks, with less conclusive research on product regulation. Despite the introduction of school food policies worldwide few large scale or national policies have been evaluated, and all included studies were from the USA and Europe. CONCLUSION: Some current school policies have been effective in improving the food environment and dietary intake in schools, but there is little evaluation of their impact on BMI. As schools have been proposed worldwide as a major setting for tackling childhood obesity it is essential that future policy evaluations measure the long term effectiveness of a range of school food policies in tackling both dietary intake and overweight and obesity.

Adherence to cervical and breast cancer programs is crucial to improving screening performance

Introduction: Cervical and breast cancer are the most common malignancies among women worldwide. Effective screening can facilitate early detection and dramatically reduce mortality rates. The interface between those screening patients and patients most needing screening is complex, and women in remote areas of rural counties face additional barriers that limit the effectiveness of cancer prevention programs. This study compared various methods to improve compliance with mass screening for breast and cervical cancer among women in a remote, rural region of Brazil. Methods: In 2003, a mobile unit was used to perform 10 156 mammograms and Papanicolaou smear tests for women living in the Barretos County region of Sao Paulo state, Brazil (consisting of 19 neighbouring cities). To reach the women, the following community outreach strategies were used: distribution of flyers and pamphlets; media broadcasts (via radio and car loudspeakers); and community healthcare agents (CHCAs) making home visits. Results: The most useful intervention appeared to be the home visits by healthcare agents or CHCAs. These agents of the Family Health Programme of the Brazilian Ministry of Health reached an average of 45.6% of those screened, with radio advertisements reaching a further 11.9%. The great majority of the screened women were illiterate or had elementary level schooling (80.9%) and were of 'poor' or 'very poor' socioeconomic class (67.2%). Conclusions: Use of a mobile screening unit is a useful strategy in developing countries where local health systems have inadequate facilities for cancer screening in underserved populations. A multimodal approach to community outreach strategies, especially using CHCAs and radio advertisements, can improve the uptake of mass screening in low-income, low-educational background female populations.

Improving sample representativeness in environmental studies: a major component for the uncertainty budget

For environmental quality assessment, INAA has been applied for determining chemical elements in small (200 mg) and large (200 g) samples of leaves from 200 trees. By applying the Ingamells` constant, the expected percent standard deviation was estimated in 0.9-2.2% for 200 mg samples. Otherwise, for composite samples (200 g), expected standard deviation varied from 0.5 to 10% in spite of analytical uncertainties ranging from 2 to 30%. Results thereby suggested the expression of the degree of representativeness as a source of uncertainty, contributing for increasing of the reliability of environmental studies mainly in the case of composite samples.

Time Constraints in the School Environment: What Does a Sleepy Student Tell Us?

In this article, we discuss school schedules and their implications in the context of chronobiological contemporary knowledge, arguing for the need to reconsider time planning in the school setting. We present anecdotal observations regarding chronobiological challenges imposed by the school system throughout different ages and discuss the effects of these schedules in terms of sleepiness and its deleterious consequences on learning, memory, and attention. Different settings (including urban vs. rural habitats) influence timing, which also depends on self-selected sleep schedules. Finally, we criticize the traditional view of a necessary strict stability of sleep-wake habits.

Improving Critical Thinking and Clinical Reasoning With a Continuing Education Course

Background: Continuing education courses related to critical thinking and clinical reasoning are needed to improve the accuracy of diagnosis. Method: This study evaluated a 4-day, 16-hour continuing education course conducted in Brazil. Thirty-nine nurses completed a pretest and a posttest consisting of two written case studies designed to measure the accuracy of nurses` diagnoses. Results: There were significant differences in accuracy from pretest to posttest for case 1 (p = .008) and case 2 (p = .042) and overall (p = .001). Conclusion: Continuing education courses should be implemented to improve the accuracy of nurses` diagnoses. J Contin Educ Nurs 2009;40(3):121-127.

Learning about knowledge management for improving environmental impact assessment in a government agency: The Western Australian experience

How does knowledge management (KM) by a government agency responsible for environmental impact assessment (EIA) potentially contribute to better environmental assessment and management practice? Staff members at government agencies in charge of the EIA process are knowledge workers who perform judgement-oriented tasks highly reliant on individual expertise, but also grounded on the agency`s knowledge accumulated over the years. Part of an agency`s knowledge can be codified and stored in an organizational memory, but is subject to decay or loss if not properly managed. The EIA agency operating in Western Australia was used as a case study. Its KM initiatives were reviewed, knowledge repositories were identified and staff surveyed to gauge the utilisation and effectiveness of such repositories in enabling them to perform EIA tasks. Key elements of KM are the preparation of substantive guidance and spatial information management. It was found that treatment of cumulative impacts on the environment is very limited and information derived from project follow-up is not properly captured and stored, thus not used to create new knowledge and to improve practice and effectiveness. Other opportunities for improving organizational learning include the use of after-action reviews. The learning about knowledge management in EIA practice gained from Western Australian experience should be of value to agencies worldwide seeking to understand where best to direct their resources for their own knowledge repositories and environmental management practice. (C) 2011 Elsevier Ltd. All rights reserved.

Improving the tracking capability of adaptive filters via convex combination

As is well known, Hessian-based adaptive filters (such as the recursive-least squares algorithm (RLS) for supervised adaptive filtering, or the Shalvi-Weinstein algorithm (SWA) for blind equalization) converge much faster than gradient-based algorithms [such as the least-mean-squares algorithm (LMS) or the constant-modulus algorithm (CMA)]. However, when the problem is tracking a time-variant filter, the issue is not so clear-cut: there are environments for which each family presents better performance. Given this, we propose the use of a convex combination of algorithms of different families to obtain an algorithm with superior tracking capability. We show the potential of this combination and provide a unified theoretical model for the steady-state excess mean-square error for convex combinations of gradient- and Hessian-based algorithms, assuming a random-walk model for the parameter variations. The proposed model is valid for algorithms of the same or different families, and for supervised (LMS and RLS) or blind (CMA and SWA) algorithms.

Improving Alzheimer`s Disease Diagnosis with Machine Learning Techniques

There is not a specific test to diagnose Alzheimer`s disease (AD). Its diagnosis should be based upon clinical history, neuropsychological and laboratory tests, neuroimaging and electroencephalography (EEG). Therefore, new approaches are necessary to enable earlier and more accurate diagnosis and to follow treatment results. In this study we used a Machine Learning (ML) technique, named Support Vector Machine (SVM), to search patterns in EEG epochs to differentiate AD patients from controls. As a result, we developed a quantitative EEG (qEEG) processing method for automatic differentiation of patients with AD from normal individuals, as a complement to the diagnosis of probable dementia. We studied EEGs from 19 normal subjects (14 females/5 males, mean age 71.6 years) and 16 probable mild to moderate symptoms AD patients (14 females/2 males, mean age 73.4 years. The results obtained from analysis of EEG epochs were accuracy 79.9% and sensitivity 83.2%. The analysis considering the diagnosis of each individual patient reached 87.0% accuracy and 91.7% sensitivity.

The role of literacy, occupation and income in dementia prevention: the Sao Paulo Ageing & Health Study (SPAH)

Background: Dementia is now a major public health issue in low- and middle-income countries, and strategies for primary prevention are needed. This study aimed to estimate the proportion of cases of dementia attributable to illiteracy, non-skilled occupation and low income, which are common, potentially modifiable social adversities that occur along the lifespan in low- and middle-income countries. Methods: This report is based on data from the Sao Paulo Ageing & Health Study (SPAH) study (N = 2003). All individuals aged 65 years and older residing within pre-defined socially deprived areas of the city of Sao Paulo, Brazil, were included. The outcome of interest was prevalent dementia. Indicators of socioeconomic position (SEP) were literacy (distal indicator), highest occupational attainment (intermediate indicator), and monthly personal income (proximal indicator). We estimated the proportion of prevalent dementia attributable to each SEP indicator (illiteracy, non-skilled occupations and low income) by calculating their population attributable fractions (PAF). Results: Dementia was more prevalent amongst participants who were illiterate, had non-skilled occupations and lower income. Illiteracy, poor occupational achievement and low income accounted for 22.0%, 38.5% and 38.5% of the cases of dementia, respectively. There was a cumulative effect of socioeconomic adversities during the lifespan, and nearly 50% of the prevalence of dementia could be potentially attributed to the combination of two or three of the socioeconomic adversities investigated. Conclusions: Public policies aimed at improving education, occupational skills and income could potentially have a role in primary prevention of dementia. Governments should address this issue in a purposeful and systematic way.

Bone Marrow Mononuclear Cell Therapy Led to Alveolar-Capillary Membrane Repair, Improving Lung Mechanics in Endotoxin-Induced Acute Lung Injury

The aim of this study was to test the hypothesis that bone marrow mononuclear cell (BMDMC) therapy led an improvement in lung mechanics and histology in endotoxin-induced lung injury. Twenty-four C57BL/6 mice were randomly divided into four groups (n = 6 each). In the acute lung injur;y (ALI) group, Escherichia coli lipopolysaccharide (LPS) was instilled intratracheally (40 mu g, IT), and control (C) mice received saline (0.05 ml, IT). One hour after the administration of saline or LPS, BMDMC (2 x 10(7) cells) was intravenously injected. At day 28, animals were anesthetized and lung mechanics [static elastance (E(st)), resistive (Delta P(1)), and viscoelastic (Delta P(2)) pressures] and histology (light and electron microscopy) were analyzed. Immunogold electron microscopy was used to evaluate if multinucleate cells were type II epithelial cells. BMDMC therapy prevented endotoxin-induced lung inflammation, alveolar collapse, and interstitial edema. In addition, BMDMC administration led to epithelial and endothelial repair with multinucleated type II pneumocytes. These histological changes yielded a reduction in lung E(st), Delta P(1), and Delta P(2) compared to ALI. In the present experimental ALI model, the administration of BMDMC yielded a reduction in the inflammatory process and a repair of epithelium and endothelium, reducing the amount of alveolar collapse, thus leading to an improvement in lung mechanics.