21 research outputs found
Profile of pharmaceutical care in primary health centers in São Bernardo do Campo, Southeastern Brazil
The effective insertion of the pharmacist into primary care is an important goal for health policies. The objective of this study was to describe and analyze pharmacists and Pharmaceutical Care in the primary health centers (UBS) of São Bernardo do Campo. Data were obtained through an interview applied to pharmacists. The instrument has three sections: (1) Pharmacist identification; (2) Pharmacist work; and (3) Pharmaceutical activities. Items in section 3 correspond to the guidelines of agencies that promote Pharmaceutical Care in the primary health system. All 24 pharmacists working in UBS in São Bernardo do Campo were interviewed. Every center dispensing medicines has a responsible pharmacist. These pharmacists are predominantly women and postgraduates. Activities of Pharmaceutical Care reported were: daily prescription analysis (75% of interviewees); monthly participation in patient groups (70.8%); monthly follow-up of pharmacotherapy adherence (58.3%); monthly participation in multiprofessional team meetings (54.2%); monthly home visits (12.5%); health education to the community (83.3%); and pharmacist consultation (37.5%). Frequency of prescription analysis and home visits was weakly associated with aspects of the pharmacist and the facility. This study showed that Pharmaceutical Services are structured in primary care in São Bernardo do Campo and many Pharmaceutical Care activities are offered in its UBS
GRAU DE CONHECIMENTO DOS PACIENTES SOBRE O TRATAMENTO: ESTRATÉGIA PARA USO RACIONAL DE MEDICAMENTOS
Síndrome do comer noturno entre estudantes universitários: aspectos da vida acadêmica estariam associados ao distúrbio alimentar?
Introduction: the critical period in the lives of college adults implies lifestyle changes such as reducing physical activity and adopting unhealthy eating habits that can result in increased body fat. Thus, college students may represent a population at increased risk for Night Eating Syndrome.
Objective: to analyze aspects of university students’ academic life, work and housing that could be associated with Night Eating Syndrome.
Methods: cross-sectional study carried out with 900 students from Architecture, Engineering, Medicine and Psychology courses at a higher education institution located in Cajazeiras, Paraíba, Brazil. Self-administered questionnaires were used for data collection: the Night Eating instrument Questionnaire (NEQ) to quantify Night Eating Syndrome (NES) behaviors and a form for variables on demographic, health, academic life, work and housing aspects.
Results: the prevalence of NES determined by the NEQ≥25 score was 16.8%. In the Engineering course, the prevalence of NES was higher in women than in men, and in the Psychology course, it was higher in men than in women. Among students with a job and who lived at home, the prevalence of the syndrome was higher for those who worked in the afternoon and lower for those who worked at night.
Conclusion: the prevalence of NES found among Brazilian university students was high (16.8%), particularly in two situations: (1) being enrolled in an undergraduate course with a predominance of students of the other sex; and (2) live with parents and work in the afternoon. These observations may be helpful in identifying subpopulations of students at increased risk for eating disorders.Introdução: o período crítico da vida de adultos universitários implica mudanças do estilo de vida como a diminuição da atividade física e a adoção de hábitos alimentares pouco saudáveis que podem resultar em aumento da gordura corporal. Assim, estudantes universitários podem representar uma população com risco aumentado para a Síndrome do Comer Noturno.
Objetivo: analisar aspectos da vida acadêmica, do trabalho e da moradia de estudantes universitários que poderiam se associar à Síndrome do Comer Noturno.
Método: estudo transversal realizado com 900 estudantes dos cursos de Arquitetura, Engenharia, Medicina e Psicologia de uma instituição de ensino superior localizada em Cajazeiras, Paraíba, Brasil. Para a coleta de dados foram usados questionários autoaplicados: o instrumento Night Eating Questionnaire (NEQ) para quantificar comportamentos da Síndrome do Comer Noturno (SCN) e um formulário para variáveis sobre aspectos demográficos, de saúde, vida acadêmica, trabalho e moradia.
Resultados: a prevalência da SCN determinada pelo escore NEQ≥25 foi 16,8%. No curso de Engenharia a prevalência da SCN foi maior nas mulheres em relação aos homens, e no curso de Psicologia, foi maior nos homens em relação as mulheres. Entre os estudantes com emprego e que moravam na casa dos pais, a prevalência da síndrome foi maior para aqueles que trabalham no período da tarde e menor para aqueles que trabalham à noite.
Conclusão: a prevalência da SCN encontrada entre os estudantes universitários brasileiros foi alta (16,8%), particularmente em duas situações: (1) estar matriculado um curso de graduação com predominância de estudantes do outro sexo; e (2) morar com os pais e trabalhar no período da tarde. Estas observações podem ser úteis na identificação de subpopulações de estudantes com risco aumentado de distúrbios de alimentação
Avaliação do polimorfismo g473a no gene da lisil oxidase como fator de risco relacionado à ocorrência de câncer de mama em mulheres brasileiras
Introduction: breast cancer is the most diagnosed type of cancer and the leading cause of death among women worldwide. Approximately 1.67 million new cases of breast cancer were diagnosed in 2012, leading to more than half a million deaths. Breast cancer accounted for 11.6% of newly diagnosed cancers (2,089 million) and 9.2% (787,000) of cancer-related deaths for both sexes and at all ages worldwide in 2018.
Objective: breast cancer, as the most diagnosed carcinoma in the world and the leading cause of death among women, is a morbidity of outstanding importance, and the object of this study is to evaluate the association between the LOX gene G473A (rs1800449) polymorphism and breast cancer occurrence, potentially establishing a new finding in the identification of risks, prevention, and care for a specific group of women.
Methods:in this retrospective cohort study, LOX G473A polymorphism frequency was assessed in 148 women with breast cancer and 245 women without breast cancer. All patients completed a questionnaire to identify possible risk factors and subsequently underwent peripheral blood collection to study the LOX gene. DNA was extracted followed by gene amplification via PCR, and the polymorphism was studied by specific fragment electrophoresis after digestion of the samples with the restriction endonuclease Pstl.
Results: this study identified the use of oral contraceptives and family history of breast cancer as risk factors for breast cancer; the G473A polymorphism in LOX was not identified as a risk factor.
Conclusion: a relationship was not observed between the LOX G473A polymorphism and the occurrence of breast cancer.Introdução: o câncer de mama é o tipo de câncer mais diagnosticado e a principal causa de morte entre as mulheres em todo o mundo. Aproximadamente 1,67 milhões de novos casos de câncer de mama foram diagnosticados em 2012, levando a mais de meio milhão de mortes. O câncer de mama foi responsável por 11,6% dos novos casos de cânceres diagnosticados (2.089 milhões) e 9,2% (787.000) das mortes relacionadas ao câncer para ambos os sexos e em todas as idades em todo o mundo em 2018.
Objetivo: o câncer de mama como o carcinoma mais diagnosticado no mundo e a principal causa de morte entre as mulheres, é uma morbidade de grande importância, sendo o objetivo deste estudo avaliar a associação entre o polimorfismo do gene LOX G473A (rs1800449) a ocorrência de câncer de mama, potencialmente estabelecendo um novo achado na identificação de riscos, prevenção, e atendimento a um grupo específico de mulheres.
Método: neste estudo de coorte retrospectivo, a frequência do polimorfismo LOX G473A foi avaliada em 148 mulheres com câncer de mama e 245 mulheres sem a doença. Todas as pacientes responderam a um questionário para identificação de possíveis fatores de risco e posteriormente realizaram coleta de sangue periférico para estudo do gene LOX. O DNA foi extraído seguido da amplificação gênica via PCR, e o polimorfismo foi estudado por eletroforese de fragmentos específicos após digestão das amostras com a endonuclease de restrição do organismo Providencia stuartii.
Resultados: este estudo identificou o uso de anticoncepcional oral e o antecedente familiar de câncer de mama como fatores de risco par a doença; o polimorfismo G473A na LOX não foi identificado como fator de risco.
Conclusão: não foi observada relação entre o polimorfismo LOX G473A e a ocorrência de câncer de mama
Brazilian isolates of Trypanosoma cruzi from humans and triatomines classified into two lineages using mini-exon and ribosomal RNA sequences
Traditional molecular and biochemical methods, such as schizodeme analysis, karyotyping, DNA fingerprinting, and enzyme electrophoretic profiles, have shown a large variability among Trypanosoma cruzi isolates. In contrast to those results, polymerase chain reaction (PCR) amplification of sequences from the 24Sα ribosomal RNA gene and from the mini-exon gene nontranscribed spacer indicated a dimorphism among T. cruzi isolates, which enabled the definition of two major parasite lineages. In the present study, 86 T. cruzi field stocks (68 isolated from humans with defined presentations of Chagas' disease and 18 from triatomines) derived from four Brazilian geographic areas were typed by the PCR assay based on the DNA sequences of the mini-exon and 24Sα rRNA genes. These stocks were ordered into the two major T. cruzi lineages. Lineage I was associated mainly with human isolates and lineage 2 with the sylvatic cycle of the parasite
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4
While the increasing availability of global databases on ecological communities has advanced our knowledge
of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In
the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of
Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus
crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced
environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian
Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by
2050. This means that unless we take immediate action, we will not be able to establish their current status,
much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost