The butterflies (Lepidoptera, Papilionoidea) of the University Campus Darcy Ribeiro (Distrito Federal, Brasil)

O cerrado brasileiro, considerado o segundo maior bioma do país em extensão territorial, encontra-se atualmente constituído apenas por fragmentos de vegetação que em conjunto representam menos de 20% de sua vegetação original. Neste trabalho nós investigamos a fauna remanescente de borboletas em fragmentos de cerrado sensu stricto e mata ciliar do campus universitário Darcy Ribeiro. No total foram encontradas 128 espécies correspondendo a aproximadamente 25% da fauna de borboletas do Distrito Federal. Alguns fatores que afetam a riqueza de espécies de borboletas nas áreas de estudo são também discutidos.The Brazilian cerrado, the second largest bioma in this country, is now constituted only by fragments of vegetation that together correspond to less than 20% of its original vegetation. This study investigates the butterfly fauna found in fragments of cerrado sensu stricto and gallery forest of the University Campus Darcy Ribeiro. A list containing 128 butterfly species, corresponding to approximately 25% of all Papilionoidea found in the Distrito Federal is presented. Some factors affecting the species richness of butterflies in the study sites are also discussed

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

Characterization and Antiproliferative Activity of a Novel 2-Aminothiophene Derivative-β-Cyclodextrin Binary System

The novel 2-aminothiophene derivative 2-amino-4,5,6,7-tetrahydrobenzo[b]thiophene-3-carbonitrile (6CN) has shown potential anti-proliferative activity in human cancer cell lines. However, the poor aqueous solubility of 6CN impairs its clinical use. This work aimed to develop binary 6CN-β-cyclodextrin (βCD) systems with the purpose of increasing 6CN solubility in water and therefore, to improve its pharmacological activity. The 6CN-βCD binary systems were prepared by physical mixing, kneading and rotary evaporation methods and further characterized by FTIR, XRD, DSC, TG and SEM. In addition, molecular modeling and phase solubility studies were performed. Finally, MTT assays were performed to investigate the cytostatic and anti-proliferative effects of 6CN-βCD binary systems. The characterization results show evident changes in the physicochemical properties of 6CN after the formation of the binary systems with βCD. In addition, 6CN was associated with βCD in aqueous solution and the solid state, which was confirmed by molecular modeling and the aforementioned characterization techniques. Phase solubility studies indicated that βCD forms stable 1:1 complexes with 6CN. The MTT assay demonstrated the cytostatic and anti-proliferative activities of 6CN-βCD binary systems and therefore, these might be considered as promising candidates for new anticancer drugs

Development, Physicochemical Characterization and In Vitro Anti-Inflammatory Activity of Solid Dispersions of α,β Amyrin Isolated from Protium Oilresin

α,β Amyrin (ABAM) is a natural mixture of pentacyclic triterpenes that has shown a variety of pharmacological properties, including anti-inflammatory effect. ABAM is isolated from Burseraceae oilresins, especially from the Protium species, which is commonly found in the Brazilian Amazon. This work aimed to develop solid dispersions (SD) of ABAM with the following hydrophilic polymers: polyvinylpyrrolidone (PVP-K30), polyethylene glycol (PEG-6000) and hydroxypropylmethylcellulose (HPMC). The SDs were prepared by physical mixture (PM), kneading (KND) and rotary evaporation (RE) methods. In order to verify any interaction between ABAM and the hydrophilic polymers, physicochemical characterization was performed by Fourier transform infrared (FTIR), scanning electron microscopy (SEM), powder X-ray diffraction (XRD), thermogravimetry (TG) and differential scanning calorimetry (DSC) analysis. Furthermore, an in vitro anti-inflammatory assay was performed with ABAM alone and as SDs with the hydrophilic polymers. The results from the characterization analysis show that the SDs were able to induce changes in the physicochemical properties of ABAM, which suggests interaction with the polymer matrix. In vitro anti-inflammatory assay showed that the SDs improved the anti-inflammatory activity of ABAM and showed no cytotoxicity. In conclusion, this study showed the potential use of SDs as an efficient tool for improving the stability and anti-inflammatory activity of ABAM without cytotoxicity

Inclusion Complexes of Copaiba (Copaifera multijuga Hayne) Oleoresin and Cyclodextrins: Physicochemical Characterization and Anti-Inflammatory Activity

Complexation with cyclodextrins (CDs) is a technique that has been extensively used to increase the aqueous solubility of oils and improve their stability. In addition, this technique has been used to convert oils into solid materials. This work aims to develop inclusion complexes of Copaifera multijuga oleoresin (CMO), which presents anti-inflammatory activity, with β-cyclodextrin (β-CD) and hydroxypropyl-β-cyclodextrin (HP-β-CD) by kneading (KND) and slurry (SL) methods. Physicochemical characterization was performed to verify the occurrence of interactions between CMO and the cyclodextrins. Carrageenan-induced hind paw edema in mice was carried out to evaluate the anti-inflammatory activity of CMO alone as well as complexed with CDs. Physicochemical characterization confirmed the formation of inclusion complex of CMO with both β-CD and HP-β-CD by KND and SL methods. Carrageenan-induced paw edema test showed that the anti-inflammatory activity of CMO was maintained after complexation with β-CD and HP-β-CD, where they were able to decrease the levels of nitrite and myeloperoxidase. In conclusion, this study showed that it is possible to produce inclusion complexes of CMO with CDs by KND and SL methods without any change in CMO’s anti-inflammatory activity