Potential wound healing effect of gel based on chicha gum, chitosan, and mauritia flexuosa oil

Wounds are considered a clinically critical issue, and effective treatment will decrease complications, prevent chronic wound formation, and allow rapid healing. The development of products based on naturally occurring materials is an efficient approach to wound healing. Natural polysaccharides can mimic the extracellular matrix and promote cell growth, thus making them attractive for wound healing. In this context, the aim of this work was to produce a gel based on chicha gum, chitosan, and Mauritia flexuosa oil (CGCHO) for wound treatment. TG and DTG analyzed the thermal behavior of the materials, and SEM investigated the surface roughness. The percentages of total phenolic compounds, flavonoids, and antioxidants were determined, presenting a value of 81.811 ± 7.257 µmol gallic acid/g Mauritia flexuosa oil, 57.915 ± 0.305 µmol quercetin/g Mauritia flexuosa oil, and 0.379 mg/mL, respectively. The anti-inflammatory was determined, presenting a value of 10.35 ± 1.46% chicha gum, 16.86 ± 1.00% Mauritia flexuosa oil, 10.17 ± 1.05% CGCHO, and 15.53 ± 0.65% chitosan, respectively. The materials were tested against Gram-negative (Klebsiella pneumoniae) and Gram-positive (Staphylococcus aureus) bacteria and a fungus (Candida albicans). The CGCHO formulation showed better antimicrobial activity against Gram-positive bacteria. In addition, an in vivo wound healing study was also performed. After 21 days of treatment, the epidermal re-epithelialization process was observed. CGCHO showed good thermal stability and roughness that can help in cell growth and promote the tissue healing process. In addition to the good results observed for the antimicrobial, antioxidant, anti-inflammatory activities and providing wound healing, they provided the necessary support for the healing process, thus representing a new approach to the wound healing process.info:eu-repo/semantics/publishedVersio

Effects of a Supraseasonal Drought on the Ecological Attributes of Plagioscion squamosissimus (Heckel, 1840) (Pisces, Sciaenidae) in a Brazilian Reservoir

The aim of this study was to evaluate the effect of a supraseasonal drought on the ecological attributes of Plagioscion squamosissimus. The fish were caught quarterly from February 2010 to November 2014 using gill nets in the reservoir of Santa Cruz, Rio Grande do Norte, Brazil. The abundance of the species was evaluated with the catch per unit effort (CPUE) metric and then correlated with the accumulated rainfall and water volume of the reservoir. The diet of the fish was evaluated using the feeding index (IAi). The proportional similarity index (PS i ) was used to evaluate the variation in the niches of the fish. The body condition was inferred through the relative condition factor, and its variation was assessed with ANOVA. A reduction in the abundance of the species that were positively correlated with the reservoir water volume was observed. The diet of the fish comprised shrimp, gastropods, fish, insects, shrimp larvae, and vegetable matter, with shrimp being the major component. PS i showed the occurrence of individual specialization during November 2013 and November 2014. The relative condition factor was not correlated with a reduction in the water volume of the reservoir. The supraseasonal drought did not affect the relative condition factor, diet, and the trophic niche, but it did affect the species abundance

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