The Brazilian National Health Agency and the Mental Health Policy in the Context of the Private Health System: developments and challenges

This work analyses the mental health policy-making activity of the Brazilian National Health Agency (ANS), responsible for controlling health insurance companies. Three points are discussed: a) the framework of an economic and private health assistance regulatory activity, b) the ANS and its regulation activity and c) the rules produced by ANS in the mental health care field. It was concluded that, despite advances like the legal obligation to ensure medical treatment to all the diseases listed in ICD-10, the inclusion of suicidal patient damage and self-inflicted damage care, care provided by a multiprofessional team, the increase in the number of sessions with a psychologist, with an occupational therapist and of psychotherapy sessions, and mental health day hospitals included as part of the services offered, the authors identified specific regulatory gaps in this area. Some issues that ANS has to solve so that it can really play its institutional role of defending the public interest in the private health system are: the regulation of co-participation and franchise mechanisms, the increasing co-participation as a limitation of psychiatric hospitalization, and the limited number of crisis intervention psychotherapy sessions.

Transcription profiling of Prss16 (Tssp) can be used to find additional peptidase genes that are candidates for self-peptide generation in the thymus

Positive selection (PS) in the thymus involves the presentation of self-peptides that are bound to MHC class II on the surface of cortical thymus epithelial cells (cTECs). Prss16 gene corresponds to one important element regulating the PS of CD4(+) T lymphocytes, which encodes Thymus-specific serine protease (Tssp), a cTEC serine-type peptidase involved in the proteolytic generation of self-peptides. Nevertheless, additional peptidase genes participating in the generation of self-peptides need to be found. Because of its role in the mechanism of PS and its expression in cTECs, the Prss16 gene might be used as a transcriptional marker to identify new genes that share the same expression profile and that encode peptidases in the thymus. To test this hypothesis, we compared the differential thymic expression of 4,500 mRNAs of wild-type (WT) C57BL/6 mice with their respective Prss16-knockout (KO) mutants by using microarrays. From these, 223 genes were differentially expressed, of which 115 had known molecular/biological functions. Four endopeptidase genes (Casp1, Casp2, Psmb3 and Tpp2) share the same expression profile as the Prss16 gene; i.e., induced in WT and repressed in KO while one endopeptidase gene, Capns1, features opposite expression profile. The Tpp2 gene is highlighted because it encodes a serine-type endopeptidase functionally similar to the Tssp enzyme. Profiling of the KO mice featured down-regulation of Prss16, as expected, along with the genes mentioned above. Considering that the Prss16-KO mice featured impaired PS, the shared regulation of the four endopeptidase genes suggested their participation in the mechanism of self-peptide generation and PS.

Complex network classification using partially self-avoiding deterministic walks

Complex networks have attracted increasing interest from various fields of science. It has been demonstrated that each complex network model presents specific topological structures which characterize its connectivity and dynamics. Complex network classification relies on the use of representative measurements that describe topological structures. Although there are a large number of measurements, most of them are correlated. To overcome this limitation, this paper presents a new measurement for complex network classification based on partially self-avoiding walks. We validate the measurement on a data set composed by 40000 complex networks of four well-known models. Our results indicate that the proposed measurement improves correct classification of networks compared to the traditional ones. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4737515]

Monitoring Drug Use Among HIV/AIDS Patients in Brazil: Should we Combine Self-Report and Urinalysis?

Illicit drug use in HIV-infected patients can be linked to impairment of physical and mental health, low health-related quality of life, and suboptimal adherence to HIV treatment. This study aimed to evaluate the correlation of self-report illicit drug use, urinalysis for cocaine and cannabis metabolites, and severity of dependence among HIV-infected patients on antiretroviral therapy (ART) in a treatment center in Brazil. Four hundred and thirty-eight outpatients of an HIV referral center were interviewed and assessed for drug use (lifetime, last year and last month). Urinalysis was performed to detect the presence of cocaine and cannabis metabolites in urine samples. Overall agreement between self-report and urinalysis was almost 68% for cannabis and higher than 85% for cocaine. Positive urinalysis was significantly associated with more than once a week cannabis (p < .0001) and cocaine (p <.0001) use during the last-month. Severity of Dependence Scale (SDS) properly predicted positive cocaine urinalysis results (area under the curve [AUC] = .81, p = .0001). Frequency of cannabis and cocaine use, SDS score degree and positive urinalysis for both drugs were correlated. Our findings suggest that positive self-report is a reliable predictor of positive urine sample both for cannabis and cocaine, but since the agreement was not perfect, there is a role for urine drug screening in the care of patients with HIV-related conditions.

Texture descriptor based on partially self-avoiding deterministic walker on networks

Texture image analysis is an important field of investigation that has attracted the attention from computer vision community in the last decades. In this paper, a novel approach for texture image analysis is proposed by using a combination of graph theory and partially self-avoiding deterministic walks. From the image, we build a regular graph where each vertex represents a pixel and it is connected to neighboring pixels (pixels whose spatial distance is less than a given radius). Transformations on the regular graph are applied to emphasize different image features. To characterize the transformed graphs, partially self-avoiding deterministic walks are performed to compose the feature vector. Experimental results on three databases indicate that the proposed method significantly improves correct classification rate compared to the state-of-the-art, e.g. from 89.37% (original tourist walk) to 94.32% on the Brodatz database, from 84.86% (Gabor filter) to 85.07% on the Vistex database and from 92.60% (original tourist walk) to 98.00% on the plant leaves database. In view of these results, it is expected that this method could provide good results in other applications such as texture synthesis and texture segmentation. (C) 2012 Elsevier Ltd. All rights reserved.

Triboelectricity: Macroscopic Charge Patterns Formed by Self-Arraying Ions on Polymer Surfaces

Tribocharged polymers display macroscopically patterned positive and negative domains, verifying the fractal geometry of electrostatic mosaics previously detected by electric probe microscopy. Excess charge on contacting polyethylene (PE) and polytetrafluoroethylene (PTFE) follows the triboelectric series but with one caveat: net charge is the arithmetic sum of patterned positive and negative charges, as opposed to the usual assumption of uniform but opposite signal charging on each surface. Extraction with n-hexane preferentially removes positive charges from PTFE, while 1,1-difluoroethane and ethanol largely remove both positive and negative charges. Using suitable analytical techniques (electron energy-loss spectral imaging, infrared microspectrophotometry and carbonization/colorimetry) and theoretical calculations, the positive species were identified as hydrocarbocations and the negative species were identified as fluorocarbanions. A comprehensive model is presented for PTFE tribocharging with PE: mechanochemical chain homolytic rupture is followed by electron transfer from hydrocarbon free radicals to the more electronegative fluorocarbon radicals. Polymer ions self-assemble according to Flory-Huggins theory, thus forming the experimentally observed macroscopic patterns. These results show that tribocharging can only be understood by considering the complex chemical events triggered by mechanical action, coupled to well-established physicochemical concepts. Patterned polymers can be cut and mounted to make macroscopic electrets and multipoles.

Physical activity counseling in primary health care in Brazil: a national study on prevalence and associated factors

Abstract Background The aim of this study was to determine the prevalence and correlates of physical activity counseling among physicians and nurses working in primary health care in Brazil. Methods A phone survey was carried out in 2011 with professionals working in primary health care in Brazil. The target sample consisted of 1,600 randomly selected primary care units covering all regions of the country. We successfully interviewed 529 professionals within the sampled units; 182 physicians and 347 nurses. The overall response rate was 49.6%. Multivariable logistic regression was used to estimate correlates of counseling in the whole sample and separately for physicians and nurses. Results The prevalence of regular physical activity counseling for at least six months was 68.9% (95% CI 64.9; 72.8) and was significantly higher among physicians compared to nurses (p < 0.05). Most professionals (93.2%) interviewed were unfamiliar with current physical activity recommendations for health. In the adjusted analysis, physical activity counseling was more frequent among those who report assessing patient’s physical activity (OR = 2.16; 95% CI 1.41; 3.29), those reporting that lack of time was not a barrier for counseling (OR = 0.62 95% CI 0.42-0.93), those who felt prepared to provide physical activity counseling (OR = 2.34; 95% CI 1.50-3.66), and those working at primary care units offering physical activity programs for patients (OR = 2.06; 95% CI 1.33-3.20). In the stratified analysis, only assessing patient’s physical activity was a significant correlate among physicians whereas assessing patient’s physical activity, feeling prepared to provide counseling and working in units with physical activity interventions were significant correlates among nurses. Conclusions Physicians and nurses deemed physical activity counseling of great importance in primary health care in Brazil. However, in order to increase the quality of counseling and the number of professionals engaging in this activity, these health teams require greater knowledge about physical activity (global recommendations for health) as well as training on the application of instruments for assessing physical activity. Moreover, sufficient time must be allowed during consultations for the counseling process, and physical activity promotion programs should be implemented within the primary health care units.

Some aspects of self-duality and generalised BPS theories

If a scalar eld theory in (1+1) dimensions possesses soliton solutions obeying rst order BPS equations, then, in general, it is possible to nd an in nite number of related eld theories with BPS solitons which obey closely related BPS equations. We point out that this fact may be understood as a simple consequence of an appropriately generalised notion of self-duality. We show that this self-duality framework enables us to generalize to higher dimensions the construction of new solitons from already known solutions. By performing simple eld transformations our procedure allows us to relate solitons with di erent topological properties. We present several interesting examples of such solitons in two and three dimensions.

Dynamic texture segmentation based on deterministic partially self-avoiding walks

Recently there has been a considerable interest in dynamic textures due to the explosive growth of multimedia databases. In addition, dynamic texture appears in a wide range of videos, which makes it very important in applications concerning to model physical phenomena. Thus, dynamic textures have emerged as a new field of investigation that extends the static or spatial textures to the spatio-temporal domain. In this paper, we propose a novel approach for dynamic texture segmentation based on automata theory and k-means algorithm. In this approach, a feature vector is extracted for each pixel by applying deterministic partially self-avoiding walks on three orthogonal planes of the video. Then, these feature vectors are clustered by the well-known k-means algorithm. Although the k-means algorithm has shown interesting results, it only ensures its convergence to a local minimum, which affects the final result of segmentation. In order to overcome this drawback, we compare six methods of initialization of the k-means. The experimental results have demonstrated the effectiveness of our proposed approach compared to the state-of-the-art segmentation methods.