Proposal for the teaching of the chemical control of supragingival biofilm

The mechanical control of supragingival biofilm is accepted as one of the most important measures to treat and prevent dental caries and periodontal diseases. Nevertheless, maintaining dental surfaces biofilm-free is not an easy task. In this regard, chemical agents, mainly in the form of mouthwashes, have been studied to help overcome the difficulties involved in the mechanical control of biofilm. The aim of this paper was to discuss proposals for the teaching of supragingival chemical control (SCC) in order to improve dentists' knowledge regarding this clinical issue. Firstly, the literature regarding the efficacy of antiseptics is presented, clearly showing that chemical agents are clinically effective in the reduction of biofilm and gingival inflammation when used as adjuvant agents to mechanical control. Thus, it is suggested that the content related to SCC be included in the curricular grid of dental schools. Secondly, some essential topics are recommended to be included in the teaching of SCC as follows: skills and competencies expected of a graduate dentist regarding SCC; how to include this content in the curricular grid; teaching-learning tools and techniques to be employed; and program content.

Vancomycin use in a brazilian teaching hospital: comparison with the Hospital Infection Controlpractices Advisory Committee Guidelines (HICPAC)

This study describes vancomycin prescribing patterns in an average complexity hospital and compare the guidelines proposed by the Hospital Infection Control Practices Advisory Committee (HICPAC). The study was conducted in a 256-bed secondary-care hospital. Data were collected of all patients given vancomycin from March 2003 to February 2004, using a standardized chart-extraction form designed. Appropriate and inappropriate use was reviewed according to the Hospital Infection Control Practices Advisory Committee (HICPAC) guidelines on prudent vancomycin use. Out of 118 prescriptions, 95 (80.5%) were considered appropriate. Out of these 95 orders, 77 (81.1%) were administered for empiric treatment of suspected Gram-positive infections, 17 (17.9%) were administered for treatment of proven Gram-positive infections (76.5% identified as Staphyloccocus aureus-like agents) and 1 (1.0%) for beta-lactam allergy. The majority of the patients (96.6%) had recently used an antimicrobial medication (3 months). The mean pre-treatment hospitalization period was 11±10 days. Out of the 118 treatments, 67 (56.8%) were for nosocomial infections. The more frequent indications for vancomycin use were pneumonia (48.3%) and primary sepsis (18.6%), accounting for more than 66% of all treatments. No restriction policy was suggested because vancomycin use was considered adequate in the majority of the treatment cases. The broad empiric use of this antimicrobial was greater than expected in the institution and its use should be revised.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

Images of a `good nurse` presented by teaching staff

Nursing is at the same time a vocation, a profession and a job. By nature, nursing is a moral endeavor, and being a `good nurse` is an issue and an aspiration for professionals. The aim of our qualitative research project carried out with 18 nurse teachers at a university nursing school in Brazil was to identify the ethical image of nursing. In semistructured interviews the participants were asked to choose one of several pictures, to justify their choice and explain what they meant by an ethical nurse. Five different perspectives were revealed: good nurses fulfill their duties correctly; they are proactive patient advocates; they are prepared and available to welcome others as persons; they are talented, competent, and carry out professional duties excellently; and they combine authority with power sharing in patient care. The results point to a transition phase from a historical introjection of religious values of obedience and service to a new sense of a secular, proactive, scientific and professional identity.

Support vector machines for detecting age-related changes in running kinematics

Age-related changes in running kinematics have been reported in the literature using classical inferential statistics. However, this approach has been hampered by the increased number of biomechanical gait variables reported and subsequently the lack of differences presented in these studies. Data mining techniques have been applied in recent biomedical studies to solve this problem using a more general approach. In the present work, we re-analyzed lower extremity running kinematic data of 17 young and 17 elderly male runners using the Support Vector Machine (SVM) classification approach. In total, 31 kinematic variables were extracted to train the classification algorithm and test the generalized performance. The results revealed different accuracy rates across three different kernel methods adopted in the classifier, with the linear kernel performing the best. A subsequent forward feature selection algorithm demonstrated that with only six features, the linear kernel SVM achieved 100% classification performance rate, showing that these features provided powerful combined information to distinguish age groups. The results of the present work demonstrate potential in applying this approach to improve knowledge about the age-related differences in running gait biomechanics and encourages the use of the SVM in other clinical contexts. (C) 2010 Elsevier Ltd. All rights reserved.

Normal Versus Pathological Voice Signals Using Wavelet Analysis and Least Squares Support-Vector Machines

State of Sao Paulo Research Foundation (FAPESP)

Remote control of CNC machines using the CyberOPC communication system over public networks

During the last few years, the evolution of fieldbus and computers networks allowed the integration of different communication systems involving both production single cells and production cells, as well as other systems for business intelligence, supervision and control. Several well-adopted communication technologies exist today for public and non-public networks. Since most of the industrial applications are time-critical, the requirements of communication systems for remote control differ from common applications for computer networks accessing the Internet, such as Web, e-mail and file transfer. The solution proposed and outlined in this work is called CyberOPC. It includes the study and the implementation of a new open communication system for remote control of industrial CNC machines, making the transmission delay for time-critical control data shorter than other OPC-based solutions, and fulfilling cyber security requirements.

Comparison Between Voltage Control Structures of Synchronous Machines

This paper compares the behaviour of two different control structures of automatic voltage regulators of synchronous machines equipped with static excitation systems. These systems have a fully controlled thyristor bridge that supplies DC current to the rotor winding. The rectifier bridge is fed by the stator terminals through a step-down transformer. The first control structure, named ""Direct Control"", has a single proportional-integral (PI) regulator that compares stator voltage setpoint with measured voltage and acts directly on the thyristor bridge`s firing angle. This control structure is usually employed in commercial excitation systems for hydrogenerators. The second structure, named ""Cascade Control"", was inspired on control loops of commercial DC motor drives. Such drives employ two PIs in a cascade arrangement, the external PI deals with the motor speed while the internal one regulates the armature current. In the adaptation proposed, the external PI compares setpoint with the actual stator voltage and produces the setpoint to the internal PI-loop which controls the field current.

Nosocomial outbreak by imipenem-resistant metallo-beta-lactamase-producing Pseudomonas aeruginosa in an adult intensive care unit in a Brazilian teaching hospital

Objective: To describe an outbreak of imipenem-resistant metallo-beta-lactamase-producing Pseudomonas aeruginosa, enzyme type bla, by horizontal transmission in patients admitted to a mixed adult ICU. Methods: A case-control study was carried out, including 47 patients (cases) and 122 patients (control) admitted to the mixed ICU of a university hospital in Minas Gerais. Brazil from November 2003 to July 2005. The infection site, risk factors, mortality, antibiotic susceptibility, metallo-beta-lactamase (MBL) production, enzyme type, and clonal diversity were analyzed, Results: A temporal/spatial relationship was detected in most patients (94%), overall mortality was 55.3%, and pneumonia was the predominant infection (85%). The majority of isolates (95%) were resistant to imipenem and other antibiotics, except for polymyxin, and showed MBL production (76.7%). Only bla SPM-1 (33%) was identified in the 15 specimens analyzed. In addition, 4 clones were identified, with a predominance of clone A (61.5%) and B (23.1%). On multivariate analysis, advanced age, mechanical ventilation, tracheostomy, and previous imipenem use were significant risk factors for imipenem-resistant P. aeruginosa infection. Conclusions: Clonal dissemination of MBL-producing P. aeruginosa strains with a spatial/temporal relationship disclosed problems in the practice of hospital infection control, low adherence to hand hygiene, and empirical antibiotic use. (C) 2008 Elsevier Espana, S.L. All rights reserved.

Information Society, Teaching, and Learning: Education Reforms in Brazil

This article examines the subject matter of learning within the context of information society, through an inquiry concerning both the reforms in education adopted in Brazil in the last thirty years and their results. It provides a revision on the explanations of school failure based on assumptions of learning problems due to cognitive and linguistic deficits. From the guidelines related with written school forms as well as the constant cultural oppression accomplished inside the school, the article claims the necessity of changing the psychological and pedagogic views that, under the label of democratic practices, determine school institutions and its daily life, by means of instrumental relations with knowledge that disregard the reading practices which are congenial to popular culture.

A Practical Teaching Course in Directed Protein Evolution Using the Green Fluorescent Protein as a Model

Protein engineering is a powerful tool, which correlates protein structure with specific functions, both in applied biotechnology and in basic research. Here, we present a practical teaching course for engineering the green fluorescent protein (GFP) from Aequorea victoria by a random mutagenesis strategy using error-prone polymerase chain reaction. Screening of bacterial colonies transformed with random mutant libraries identified GFP variants with increased fluorescence yields. Mapping the three-dimensional structure of these mutants demonstrated how alterations in structural features such as the environment around the fluorophore and properties of the protein surface can influence functional properties such as the intensity of fluorescence and protein solubility.

History teaching today: wanderings, gains and losses

This article analyzes traditions of debate about the teaching of history in Brazil since the 1964-1984 dictatorship. It discusses the changes, continuities, achievements and losses in the history of the discipline. It emphasizes the importance of school culture, the necessary continuity of the school as an institution and dialogue with non-school forms of education.

An fMRI Normative Database for Connectivity Networks Using One-Class Support Vector Machines

The application of functional magnetic resonance imaging (fMRI) in neuroscience studies has increased enormously in the last decade. Although primarily used to map brain regions activated by specific stimuli, many studies have shown that fMRI can also be useful in identifying interactions between brain regions (functional and effective connectivity). Despite the widespread use of fMRI as a research tool, clinical applications of brain connectivity as studied by fMRI are not well established. One possible explanation is the lack of normal pattern, and intersubject variability-two variables that are still largely uncharacterized in most patient populations of interest. In the current study, we combine the identification of functional connectivity networks extracted by using Spearman partial correlation with the use of a one-class support vector machine in order construct a normative database. An application of this approach is illustrated using an fMRI dataset of 43 healthy Subjects performing a visual working memory task. In addition, the relationships between the results obtained and behavioral data are explored. Hum Brain Mapp 30:1068-1076, 2009. (C) 2008 Wiley-Liss. Inc.

The impact of functional connectivity changes on support vector machines mapping of fMRI data

Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.

Teaching Psychodynamics to Psychiatric Residents through Psychiatric Outpatient Interviews

Objective: This study evaluates whether a course that was designed for first-year psychiatric residents and that specifically addressed psychodynamic principles fostered residents` progress in knowledge, skills, and attitudes regarding these concepts. Methods: The course was given in the 2005 academic year to all residents (N = 18) in their first psychiatric postgraduate year at the Department and Institute of Psychiatry, University of Sao Paulo, Brazil. The residents were assessed in the first and last sessions of the course through a written test that was blindly rated by two independent judges. Residents were also interviewed to observe whether psychodynamic concepts had been integrated into actual practice. Their responses were subjected to content analysis. Significance was tested using analysis of variance or nonparametric tests when necessary. Agreement between the judges was tested using intraclass correlation coefficients. Results: The judges demonstrated a high level of agreement. The difference in mean scores before and after the course was such that the total score increased by a mean of 2.5 points (total test score was 10 points). Additionally, residents started to undergo personal psychotherapy after the course. They reported that this course had markedly improved their relationship with patients. They emphasized the opportunities for self-reflection and gaining insights into themselves and patient treatment issues. Conclusion: This initial study indicates that this educational method can effectively promote psychodynamic knowledge, skills, and appropriate attitudes for managing psychiatric outpatients among residents. The course was very well received by the residents, and a similar method can easily be instituted within other residency programs that pursue integrated teaching methods.