Anatomical Organization of Urocortin 3-Synthesizing Neurons and Immunoreactive Terminals in the Central Nervous System of Non-Human Primates [Sapajus spp.]

Urocortin 3 (UCN3) is a neuropeptide member of the corticotropin-releasing factor (CRF) peptide family that acts as a selective endogenous ligand for the CRF, subtype 2 (CRF2) receptor. Immunohistochemistry and in situ hybridization data from rodents revealed UCN3-containing neurons in discrete regions of the central nervous system (CNS), such as the medial preoptic nucleus, the rostral perifornical area (PFA), the medial nucleus of the amygdala and the superior paraolivary nucleus. UCN3-immunoreactive (UCN3-ir) terminals are distributed throughout regions that mostly overlap with regions of CRF2 messenger RNA (mRNA) expression. Currently, no similar mapping exists for non-human primates. To better understand the role of this neuropeptide, we aimed to study the UCN3 distribution in the brains of New World monkeys of the Sapajus genus. To this end, we analyzed the gene and peptide sequences in these animals and performed immunohistochemistry and in situ hybridization to identify UCN3 synthesis sites and to determine the distribution of UCN3-ir terminals. The sequencing of the Sapajus spp. UCN3-coding gene revealed 88% and 65% identity to the human and rat counterparts, respectively. Additionally, using a probe generated from monkey cDNA and an antiserum raised against human UCN3, we found that labeled cells are mainly located in the hypothalamic and limbic regions. UCN3-ir axons and terminals are primarily distributed in the ventromedial hypothalamic nucleus (VMH) and the lateral septal nucleus (LS). Our results demonstrate that UCN3-producing neurons in the CNS of monkeys are phylogenetically conserved compared to those of the rodent brain, that the distribution of fibers agrees with the distribution of CRF2 in other primates and that there is anatomical evidence for the participation of UCN3 in neuroendocrine control in primates

Chronic inflammatory diseases, subclinical atherosclerosis, and cardiovascular diseases: Design, objectives, and baseline characteristics of a prospective case-cohort study ‒ ELSA-Brasil

Objectives: This analysis describes the protocol of a study with a case-cohort to design to prospectively evaluate the incidence of subclinical atherosclerosis and Cardiovascular Disease (CVD) in Chronic Inflammatory Disease (CID) participants compared to non-diseased ones. Methods: A high-risk group for CID was defined based on data collected in all visits on self-reported medical diagnosis, use of medicines, and levels of high-sensitivity C-Reactive Protein >10 mg/L. The comparison group is the Aleatory Cohort Sample (ACS): a group with 10% of participants selected at baseline who represent the entire cohort. In both groups, specific biomarkers for DIC, markers of subclinical atherosclerosis, and CVD morbimortality will be tested using weighted Cox. Results: The high-risk group (n = 2,949; aged 53.6 ± 9.2; 65.5% women) and the ACS (n=1543; 52.2±8.8; 54.1% women) were identified. Beyond being older and mostly women, participants in the high-risk group present low average income (29.1% vs. 24.8%, p < 0.0001), higher BMI (Kg/m2) (28.1 vs. 26.9, p < 0.0001), higher waist circumference (cm) (93.3 vs. 91, p < 0.0001), higher frequencies of hypertension (40.2% vs. 34.5%, p < 0.0001), diabetes (20.7% vs. 17%, p = 0.003) depression (5.8% vs. 3.9%, p = 0.007) and higher levels of GlycA a new inflammatory marker (p < 0.0001) compared to the ACS. Conclusions: The high-risk group selected mostly women, older, lower-income/education, higher BMI, waist circumference, and of hypertension, diabetes, depression, and higher levels of GlycA when compared to the ACS. The strategy chosen to define the high-risk group seems adequate given that multiple sociodemographic and clinical characteristics are compatible with CID

Basin-wide variation in tree hydraulic safety margins predicts the carbon balance of Amazon forests

Funding: Data collection was largely funded by the UK Natural Environment Research Council (NERC) project TREMOR (NE/N004655/1) to D.G., E.G. and O.P., with further funds from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES, finance code 001) to J.V.T. and a University of Leeds Climate Research Bursary Fund to J.V.T. D.G., E.G. and O.P. acknowledge further support from a NERC-funded consortium award (ARBOLES, NE/S011811/1). This paper is an outcome of J.V.T.’s doctoral thesis, which was sponsored by CAPES (GDE 99999.001293/2015-00). J.V.T. was previously supported by the NERC-funded ARBOLES project (NE/S011811/1) and is supported at present by the Swedish Research Council Vetenskapsrådet (grant no. 2019-03758 to R.M.). E.G., O.P. and D.G. acknowledge support from NERC-funded BIORED grant (NE/N012542/1). O.P. acknowledges support from an ERC Advanced Grant and a Royal Society Wolfson Research Merit Award. R.S.O. was supported by a CNPq productivity scholarship, the São Paulo Research Foundation (FAPESP-Microsoft 11/52072-0) and the US Department of Energy, project GoAmazon (FAPESP 2013/50531-2). M.M. acknowledges support from MINECO FUN2FUN (CGL2013-46808-R) and DRESS (CGL2017-89149-C2-1-R). C.S.-M., F.B.V. and P.R.L.B. were financed by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES, finance code 001). C.S.-M. received a scholarship from the Brazilian National Council for Scientific and Technological Development (CNPq 140353/2017-8) and CAPES (science without borders 88881.135316/2016-01). Y.M. acknowledges the Gordon and Betty Moore Foundation and ERC Advanced Investigator Grant (GEM-TRAITS, 321131) for supporting the Global Ecosystems Monitoring (GEM) network (gem.tropicalforests.ox.ac.uk), within which some of the field sites (KEN, TAM and ALP) are nested. The authors thank Brazil–USA Collaborative Research GoAmazon DOE-FAPESP-FAPEAM (FAPESP 2013/50533-5 to L.A.) and National Science Foundation (award DEB-1753973 to L. Alves). They thank Serrapilheira Serra-1709-18983 (to M.H.) and CNPq-PELD/POPA-441443/2016-8 (to L.G.) (P.I. Albertina Lima). They thank all the colleagues and grants mentioned elsewhere [8,36] that established, identified and measured the Amazon forest plots in the RAINFOR network analysed here. The authors particularly thank J. Lyod, S. Almeida, F. Brown, B. Vicenti, N. Silva and L. Alves. This work is an outcome approved Research Project no. 19 from ForestPlots.net, a collaborative initiative developed at the University of Leeds that unites researchers and the monitoring of their permanent plots from the world’s tropical forests [61]. The authros thank A. Levesley, K. Melgaço Ladvocat and G. Pickavance for ForestPlots.net management. They thank Y. Wang and J. Baker, respectively, for their help with the map and with the climatic data. The authors acknowledge the invaluable help of M. Brum for kindly providing the comparison of vulnerability curves based on PAD and on PLC shown in this manuscript. They thank J. Martinez-Vilalta for his comments on an early version of this manuscript. The authors also thank V. Hilares and the Asociación para la Investigación y Desarrollo Integral (AIDER, Puerto Maldonado, Peru); V. Saldaña and Instituto de Investigaciones de la Amazonía Peruana (IIAP) for local field campaign support in Peru; E. Chavez and Noel Kempff Natural History Museum for local field campaign support in Bolivia; ICMBio, INPA/NAPPA/LBA COOMFLONA (Cooperativa mista da Flona Tapajós) and T. I. Bragança-Marituba for the research support.Tropical forests face increasing climate risk1,2, yet our ability to predict their response to climate change is limited by poor understanding of their resistance to water stress. Although xylem embolism resistance thresholds (for example, Ψ50) and hydraulic safety margins (for example, HSM50) are important predictors of drought-induced mortality risk3-5, little is known about how these vary across Earth's largest tropical forest. Here, we present a pan-Amazon, fully standardized hydraulic traits dataset and use it to assess regional variation in drought sensitivity and hydraulic trait ability to predict species distributions and long-term forest biomass accumulation. Parameters Ψ50 and HSM50 vary markedly across the Amazon and are related to average long-term rainfall characteristics. Both Ψ50 and HSM50 influence the biogeographical distribution of Amazon tree species. However, HSM50 was the only significant predictor of observed decadal-scale changes in forest biomass. Old-growth forests with wide HSM50 are gaining more biomass than are low HSM50 forests. We propose that this may be associated with a growth-mortality trade-off whereby trees in forests consisting of fast-growing species take greater hydraulic risks and face greater mortality risk. Moreover, in regions of more pronounced climatic change, we find evidence that forests are losing biomass, suggesting that species in these regions may be operating beyond their hydraulic limits. Continued climate change is likely to further reduce HSM50 in the Amazon6,7, with strong implications for the Amazon carbon sink.Publisher PDFPeer reviewe

Resistance of Leishmania (Leishmania) amazonensis and Leishmania (Viannia) braziliensis to nitric oxide correlates with disease severity in Tegumentary Leishmaniasis

BACKGROUND: Nitric oxide (NO(•)) plays a pivotal role as a leishmanicidal agent in mouse macrophages. NO(• )resistant Escherichia coli and Mycobacterium tuberculosis have been associated with a severe outcome of these diseases. METHODS: In this study we evaluated the in vitro toxicity of nitric oxide for the promastigote stages of Leishmania (Viannia) braziliensis and Leishmania (Leishmania) amazonensis parasites, and the infectivity of the amastigote stage for human macrophages. Parasites were isolated from patients with cutaneous, mucosal or disseminated leishmaniasis, and NO(• )resistance was correlated with clinical presentation. RESULTS: Seventeen isolates of L. (L.) amazonensis or L. (V.) braziliensis promastigotes were killed by up to 8 mM of more of NaNO(2 )(pH 5.0) and therefore were defined as nitric oxide-susceptible. In contrast, eleven isolates that survived exposure to 16 mM NaNO(2 )were defined as nitric oxide-resistant. Patients infected with nitric oxide-resistant Leishmania had significantly larger lesions than patients infected with nitric oxide-susceptible isolates. Furthermore, nitric oxide-resistant L. (L.) amazonensis and L. (V.) braziliensis multiplied significantly better in human macrophages than nitric oxide-susceptible isolates. CONCLUSION: These data suggest that nitric oxide-resistance of Leishmania isolates confers a survival benefit for the parasites inside the macrophage, and possibly exacerbates the clinical course of human leishmaniasis