Synthesis and structural characterization of new Piano-stool Ruthenium(II) complexes bearing 1-Butylimidazole heteroaromatic ligand

New cationic ruthenium(II) complexes with the formula [Ru(eta(5)-C5H5)(LL)(1-BuIm)] [Z], with (LL) = 2PPh(3) or DPPE, and Z = CF3SO3-, PF6-, BPh4-, have been synthesized and fully characterized. Spectroscopic and electrochemical studies revealed that the electronic properties of the coordinated 1-butylimidazole were clearly influenced by the nature of the phosphane coligands (LL) and also by the different counter ions. The solid state structures of the six complexes determined by X-ray crystallographic studies, confirmed the expected distorted three-legged piano stool structure. However the geometry of the 1-butylimidazole ligand was found considerably different in all six compounds, being governed by the stereochemistry of the mono and bidentate coligands (PPh3 or DPPE)

Meglumine antimoniate and miltefosine combined with allopurinol sustain pro-inflammatory immune environments during canine leishmaniosis treatment

Research Areas: Veterinary SciencesCanine leishmaniosis (CanL) caused by Leishmania infantum is a zoonotic disease of global concern. Antileishmanial drug therapies commonly used to treat sick dogs improve their clinical condition, although when discontinued relapses can occur. Thus, the current study aims to evaluate the effect of CanL treatments in peripheral blood, lymph node, and bone marrow cytokine profile associated with clinical recovery. Two groups of six dogs diagnosed with CanL were treated with miltefosine combined with allopurinol and meglumine antimoniate combined with allopurinol (MT+A and MG+A), respectively. At diagnosis and after treatment, during a 3-month follow-up, clinical signs, hematological and biochemical parameters, urinalysis results and antileishmanial antibody titers were registered. Furthermore, peripheral blood, popliteal lymph node, and bone marrow samples were collected to assess the gene expression of IL-2, IL-4, IL-5, IL-10, IL-12, TNF-alpha, TGF-beta, and IFN-gamma by qPCR. In parallel, were also evaluated samples obtained from five healthy dogs. Both treatment protocols promoted the remission of clinical signs as well as normalization of hematological and biochemical parameters and urinalysis values. Antileishmanial antibodies returned to non-significant titers in all dogs. Sick dogs showed a generalized upregulation of IFN-gamma and downregulation of IL-2, IL-4, and TGF-beta, while gene expression of IL-12, TNF-alpha, IL-5, and IL-10 varied between groups and according to evaluated tissue. A trend to the normalization of cytokine gene expression was induced by both miltefosine and meglumine antimoniate combined therapies. However, IFN-gamma gene expression was still up-regulated in the three evaluated tissues. Furthermore, the effect of treatment in the gene expression of cytokines that were not significantly changed by infection, indicates that miltefosine and meglumine antimoniate combined therapy directly affects cytokine generation. Both combined therapies are effective in CanL treatment, leading to sustained pro-inflammatory immune environments that can compromise parasite survival and favor dogs' clinical cure. In the current study, anti-inflammatory and regulatory cytokines do not seem to play a prominent role in CanL or during clinical recovery.info: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 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

First heterobimetallic Cu(i)-dppf complexes designed for anticancer applications: synthesis, structural characterization and cytotoxicity

A new family of eight heterobimetallic Cu(i)-dppf complexes of general formula [Cu(dppf)L][BF4] with dppf = 1,1 '-bis(diphenylphosphino)ferrocene and L representing N,N-, N,O- and N,S-heteroaromatic bidentate ligands have been synthesized and fully characterized by classical analytical, spectroscopic and electrochemical methods. The single crystal structures of [Cu(dppf)(pBI)][BF4] (6), [Cu(dppf)(dpytz)][BF4] (7) and [Cu(dppf)(5-Aphen)][BF4] (8) complexes (where pBI = 2-(2-pyridyl)benzimidazole, dpytz = 3-(2-pyridyl)-5,6-diphenyl-1,2,4-triazine and 5-Aphen = 1,10-phenanthrolin-5-amine) were determined by X-ray diffraction studies. Cytotoxicity of all complexes was evaluated in two human breast adenocarcinoma cell lines (MCF7 and MDAMB231). All the complexes exhibit high cytotoxicity against both human breast cancer cells with IC50 values far lower than those found for the antitumor drug cisplatin in the same cell lines. The IC50 values on primary healthy fibroblasts are of the same order of magnitude as those found for the tumoral cells.info:eu-repo/semantics/publishedVersio