Factors Relates To A Non Medical Accession By Hipoglycemics Patients With Oral Diabetes Mellitus Type 2

Diabetes mellitus type 2 can be defied as a syndrome of multiple etiologies and currently, it is estimated that in the world exists about 150 million patients with DM, and that number could double until 2025. Non-adherence to treatment is a diffiulty in effective assistance to individuals. This study aims to understand the factors related to non-adherence to oral hypoglycemic drug in patients with type 2 mellitus diabetes It is an integrative review, held in the databases SciELO, PubMed, MEDLINE and LILACS, using the descriptors DeCS (MeSH) - Descriptors in Health Sciences: medication adherence, type 2 diabetes and chronic disease. The selection respected inclusion/exclusion criteria previously listed considering the last six years. 108 articles of which 18 met the criteria were identifid. Among the factors that are related to medication accession are: gender, age, education, income, information about the disease and the medication, comorbidities, side effects and the time of diagnosis. It become necessary in health education strategies to take into consideration the various personal differences

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

Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences

The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & Nemésio 2007; Donegan 2008, 2009; Nemésio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on 18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based researchers who signed it in the short time span from 20 September to 6 October 2016

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

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others

Applicability, sensitivity, specificity and accuracy of the Depressive Cognition Scale: A systematic review with meta-analysis/ Aplicabilidade, sensibilidade, especificidade e acurácia do Depressive Cognition Scale: Uma revisão sistemática com metanálise

Background: Depression can influence the treatment of diabetes mellitus, because it causes physiological alterations in the neurochemical and hormonal functions, which could cause hyperglycemic effects. Methods: This systematic review with meta-analysis follows the recommendations of the Cochrane Handbook and Prisma. Inclusion/exclusion criteria that had been previously selected for the sample were adopted by using the MEDLINE/PubMed, LILACS/BIREME, SciELO, ScienceDirect, Cochrane Library and Scopus databases, through the keywords “depression”, “risk factors” and “diabetes mellitus” in DeCS/MeSH, and “depressive cognition scale”, which were combined using the Boolean operator “AND”. The statistical analysis used the Bioestat 5.0 and Review Manager 5.3 programs. Results: With regard to the results, 26,292 publications were identified; however, after submitting them to the criteria and to the reviewers’ analyses, only 12 studies remained. Sensitivity and specificity were found higher than 78%, which is statistically significant. The test accuracy represented 0.79, thus it confirmed the applicability of the instrument. The combined Odds Ratio value presented a result of 6.3 CI (5.7 – 7.1). This fact shows the great association between diabetes and depression and the importance of the Depressive Cognition Scale in patients with diabetes mellitus. The p-value obtained (<0.0001) seemed to be statistically significant for the analyzed data. Limitations: Scarcity of studies assessing the Depression Cognitive Scale about diabetes mellitus. Conclusions: The Depressive Cognition Scale presents statistically significant sensitivity, specificity, and accuracy. This scale is a reliable and applicable tool for screening and identification of depression risk factors in diabetic patients

First comprehensive study on total determination of nutritional elements in the fruit of the Campomanesia adamantium (Cambess.): Brazilian cerrado plant

Introduction: Composition of fruits and leaves of Campomanesia adamantium (Cambess.) O. Berg commonly called guavira are used in dietary or as a mode of treatment of variety of ailments in indigenous and urban populations in the city of the Campo Grande, State of Mato Grosso do Sul, Brazil. However, comprehensive studies on their mineral composition are scarce. Objective: In the present study, evaluation of mineral contents (Na, K, Ca, Mg, P, Fe, Zn, Ni, Mn, Co, Cu, Mo, Cr, Si and Al) from peel, pulp and seeds of guavira was carried out. Method: The peel, pulp and seeds of guavira were studied by ICP-OES with microwave digestion. The contents of the elements in the parts of the guavira, were compared to the Recommended Dietary Allowance (RDA), values Adequate Intake (AI) and tolerable upper intake levels (ULs). Results: The results are considered in terms of the utility of the natural herbal medicaments as rich (Cu, P, Cr and Mo) or a source of minerals indispensable for proper functioning of the human organism. The concentration of elements in seeds, pulp and peel the guavira was compared with value of UL and does not cause toxicity. The concentration of elements K, Ca, Na, P are found present at the major level in peel, pulp and seeds of fruit. The contents of Chromium (Cr) were reportedly found higher than the permissible levels as recommended by the WHO. Conclusion: The lack of knowledge of the elemental constituents of several species of medicinal plants often poses human lives at risk, these elements can also be dangerous and toxic, and involves global health problem. The gaps in knowledge about the level of contents in the Campomanesia adamantium (Cambess.) O. Berg was completed in this work. The data obtained would serve as a tool for deciding the dosage of prepared from this plant with medicinal and nutritional purposes. Keywords: Medicinal plants; Guavira; Inductively coupled plasma mass spectrometry

USO DAS TECNOLOGIAS DIGITAIS COMO SUPORTE PARA A APRENDIZAGEM NA ERA DA EDUCAÇÃO E INDÚSTRIA 4.0 - vol. 1

No primeiro volume discutimos as bases teóricas necessárias para o uso adequado das tecnologias digitais de informação e comunicação, como suporte ao processo de aprendizagem. Nele, procuramos dar o embasamento teórico ao uso dessas tecnologias por professores, e nortear quais competências os aprendentes deveriam ter adquirido ao finalizar seu ciclo fundamental e médio. Também procuramos desmistificar a visão corrente de que design instrucional sirva apenas para cursos de treinamento. Nossa crença é de que, sem a prática do design instrucional, seja impossível o planejamento inter ou transdisciplinar e a aprendizagem híbrida