Novas Publicações do inctAmbTropic
Atualizado: 27 de Ago de 2020
Três novos trabalhos foram publicados em periódicos internacionais apresentando resultados do inctAmbTropic. Lembramos que apenas os trabalhos que declaram nos agradecimentos a chancela do inctAmbTropic são computados como produção acadêmica do Instituto.
Cavalcante-Silva et al. 2013. Spasmolytic Effect of Caulerpine Involves Blockade of Ca2+ Influx on Guinea Pig Ileum. Marine Drugs , 11, 1553-1564; doi:10.3390/md11051553. Impact Factor: 3,174
In this work, we investigated the spasmolytic effect of caulerpine, a bisindole alkaloid isolated from marine algae of the Caulerpa genus, on guinea pig ileum. Our findings indicated that caulerpine inhibited phasic contractions induced by carbachol (IC50 = 7.0 ± 1.9 × 10−5 M), histamine (IC50 = 1.3 ± 0.3 × 10−4 M) and serotonin (IC50 = 8.0 ± 1.4 × 10−5 M) in a non-selective manner. Furthermore, caulerpine concentration-dependently inhibited serotonin-induced cumulative contractions (pD′2 = 4.48 ± 0.08), shifting the curves to the right with Emax reduction and slope of 2.44 ± 0.21, suggesting a noncompetitive antagonism pseudo-irreversible. The alkaloid also relaxed the ileum pre-contracted by KCl (EC50 = 9.0 ±0.9 ×10−5 M) and carbachol (EC50 = 4.6 ±0.7 ×10−5 M) in a concentration-dependent manner. This effect was probably due to inhibition of Ca2+ influx through voltage-gated calcium channels (CaV), since caulerpine slightly inhibited the CaCl2-induced contractions in depolarizing medium without Ca2+, shifting the curves to the right and with Emax reduction. According to these results, the spasmolytic effect of caulerpine on guinea pig ileum seems to involve inhibition of Ca2+ influx through CaV. However, other mechanisms are not discarded. Impact Factor: 3,978 (2012); 5-Year Impact Factor: 3,911 (2012)Link: http://www.mdpi.com/1660-3397/11/5/1553
Araujo et al. 2013. Nutrient Input and CO2 Flux of a Tropical Coastal Fluvial System with High Population Density in the Northeast Region of Brazil. Journal of Water Resource and Protection, 2013, 5, 362-375. Impact factor: 0,41 com base no ISI Web of Knowledge.
The carbon dioxide flux through the air-water interface of coastal freshwater ecosystems must be quantified to under- stand the regional balances of carbon and its transport through coastal and estuarine regions. The variations in air-sea CO2 fluxes in nearshore ecosystems can be caused by the variable influence of rivers. In the present study, the amount of carbon emitted from a tropical coastal river was estimated using climatological and biogeochemical measurements (2002-2010) obtained from the basin of the Capibaribe River, which is located in the most populous and industrialized area of the northeast region of Brazil. The results showed a mean CO2 flux of +225 mmol·m−2·d−1, mainly from organic material from the untreated domestic and industrial wastewaters that are released into the river. This organic material increased the dissolved CO2 concentration in the river waters, leading to a partial pressure of CO2 in the aquatic environment that reached 31,000 μatm. The months of April, February and December (the dry period) showed the largest monthly means for the variables associated with the carbonate system ( HCO− , DIC, CO , CO2− , TA, temperature and pH). This status reflects the state of permanent pollution in the basin of the Capibaribe River, due, in particular, to the discharge of untreated domestic wastewater, which results in the continuous mineralization of organic material. This mineralization significantly increases the dissolved CO2 content in the estuarine and coastal waters, which is later re-leased to the atmosphere. Impact factor: 0,41 com base no ISI Web of Knowledge.Link: http://www.scirp.org/journal/jwarp/
Lins et al (2013). Prediction of sea surface temperature in the tropical Atlantic by support vector machinesComputational Statistics and Data Analysis 61 (2013) 187–198. Impact Factor: 1,304. 5-Year Impact Factor: 1, 449
The Sea Surface Temperature (SST) is one of the environmental indicators monitored by buoys of the Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) Project. In this work, a year-ahead prediction procedure based on SST knowledge of previous periods is proposed and coupled with Support Vector Machines (SVMs). The proposed procedure is focused on seasonal and intraseasonal aspects of SST. Data from PIRATA buoys are used in various ways to feed the SVM models: with raw data, using information about the SST slopes and by means of SST curvatures. The influence of these data handling strategies over the predictive capacity of the proposed methodology is discussed. Additionally, the forecasts’ accuracy is evaluated as the number of years considered in the SVM training phase increases. The raw data and the curvatures presented quite similar performances, they are more efficient than the slopes; the respective Mean Absolute Percentage Error (MAPE) values do not exceed 2% and all Mean Absolute Errors (MAEs) are lower than 0.37 °C. Besides, as the number of years considered in the training set increases, the MAPE and MAE values tend to stabilize. Impact Factor: 1,304. 5-Year Impact Factor: 1, 449 Link: http://www.sciencedirect.com/science/article/pii/S0167947312004240