Physicochemical assessment of an orabase formulation of Libidibia ferrea L: Avaliação físico-química de uma formulação orabase de Libidibia ferrea L

The aim of the study was to control the physicochemical quality of an orabase formulation of L. ferrea L. An experimental, in vitro, controlled study was carried out as follows: centrifuge tests, pH, density, rheological behavior at room temperature (25.0 ± 2.0 °C), microbiological control by determining the total number of aerobic microorganisms, yeast growth, and organoleptic characteristics. The storage conditions were as follows: light room (±25.9°C), dark room (±28.8°C), refrigerator (± 2 to 8°C), and the experimental periods were 0, 30 and 60 days. In the centrifuge test, the separation of 1 oily phase (liquid and transparent) was observed in all storage conditions and times tested; in the pH test, the formulation remained stable with pH variations between 6.01 and 6.67, but there was no statistically significant difference at all times and conditions tested. The rheological behavior in terms of viscosity revealed that time and storage conditions did not alter the samples and the mean standard values related to rotation were 6 mPa.SNa (5111.9 ±11), 12 mPa.S (2555.2 ±7), 30 mPa.S (1023.9 ±2) and 60 mPa.S (512.5 ±4). The assessment of contaminants revealed no growth of contaminants in the storage conditions and times tested. As for the organoleptic characteristics, the samples showed no changes throughout the time and storage conditions. The formulation is physically and chemically stable under all storage conditions and times tested, proving to be suitable for extemporaneous formulations

DESAFIOS CLÍNICOS NA ENCEFALOPATIA HEPÁTICA: INTEGRAÇÃO DE CUIDADOS PSIQUIÁTRICOS E CIRÚRGICOS NO TRATAMENTO

This study addresses the integration of psychiatric and surgical care in managing hepatic encephalopathy, highlighting its importance in the multidisciplinary approach to the condition. The aim is to investigate the effectiveness of this approach in improving clinical outcomes for affected patients. The methodology involved a detailed literature review, using specific descriptors and rigorous inclusion criteria to identify relevant studies. The results highlight a significant improvement in patients' quality of life and a reduction in complications associated with hepatic encephalopathy with the multidisciplinary approach. In conclusion, this collaborative approach proves to be crucial for a more comprehensive and effective management of hepatic encephalopathy, promoting better clinical outcomes and higher quality of life.Este estudo aborda a integração de cuidados psiquiátricos e cirúrgicos na gestão da encefalopatia hepática, destacando sua importância na abordagem multidisciplinar da condição. O objetivo é investigar a eficácia dessa abordagem para melhorar os desfechos clínicos dos pacientes afetados. A metodologia envolveu uma revisão detalhada da literatura, utilizando descritores específicos e critérios de inclusão rigorosos para identificar estudos relevantes. Os resultados destacam uma melhoria significativa na qualidade de vida dos pacientes e uma redução nas complicações associadas à encefalopatia hepática com a abordagem multidisciplinar. Em conclusão, essa abordagem colaborativa demonstra ser fundamental para uma gestão mais abrangente e eficaz da encefalopatia hepática, promovendo melhores resultados clínicos e uma maior qualidade de vida

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

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

Effect of a Copaiba Oil-Based Dental Biomodifier on the Inhibition of Metalloproteinase in Adhesive Restoration

Aim. This study sets out to evaluate the antiproteolytic activity of copaiba oil-based emulsion at the resin/dentin adhesive interface union formed with conventional and self-etching adhesives systems. Methods. At in situ zymography, 30 teeth were sectioned 2 mm below the enamel-dentin junction; a smear layer was standardized and subdivided into four groups. Gelatin conjugated with fluorescein was used and taken to the fluorescence microscope for evaluation. In cytotoxicity, the Trypan Blue method was used at four different time points. The tested groups were (G1) control with distilled water; (G2) 2% chlorhexidine (CLX); (G3) emulsion based on copaiba oil (EC) 10% + X; (G4) 10% EC + Y; and (G5) EC 10% alkaline. The zymographic assay used the same groups described, but in 30 seconds and 10 and 20 minutes. HT1080 cells were incubated and submitted to electrophoresis. The gel was analyzed using ImageJ software. Mann–Whitney and Kruskal–Wallis tests were used in the statistical analysis (p<0.05). Results. ECs showed higher cell viability in the cytotoxicity test and showed a significant difference in 10 and 20 minutes. In the zymographic assay, alkaline EC reduced 67% of MMP-2 activity and 44% of MMP-9 compared to 2% chlorhexidine. At in situ zymography in qualitative evaluation, all groups tested showed inhibition of activity in metalloproteinases. Conclusion. EC showed activity in the inhibition of metalloproteinases in vitro and in situ, especially the alkaline one. The survey shows the possibility of using ECs, a product from Amazonian biodiversity, as a biomodifier in dentistry