Your search

Parental nutrient reserves are directly related to reproductive performance in sea cucumbers. This study focused on the lipid requirements of male and female sea cucumbers Apostichopus japonicus during the reproductive stage and analyzed their physiological responses to a high-fat diet (HFD). The intestinal lipid metabolites and microbiome profile changed significantly in animals fed with the HFD, as given by an upregulation of metabolites related to lipid metabolism and an increase in the predominance of Proteobacteria in the microbiome, respectively. The metabolic responses of male and female sea cucumbers to the HFD differed, which in turn could have triggered sex-related differences in the intestinal microbiome. These results suggest that the lipid content in diets can be differentially adjusted for male and female sea cucumbers to improve nutrition and promote reproduction. This data contributes to a better understanding of the reproductive biology and sex differences of sea cucumbers.

Reproduction of the sea cucumber Apostichopus japonicus is critical for aquaculture production. Gonadal development is the basis of reproduction, and lipids, which are among the main nutrients required for gonadal development, directly affect reproduction. We investigated whether gonadal and intestinal lipid metabolism differed between male and female A. japonicus. Transcriptome analysis of the intestines of sexually mature male and female wild-caught individuals revealed differences in gene expression, with 27 and 39 genes being up-regulated in females and males, respectively. In particular, the expression of the fatty acid synthase gene was higher in males than in females. Metabolome analysis of the gonads identified 141 metabolites that were up-regulated and 175 metabolites that were down-regulated in the testes compared with the ovaries in the positive/negative mode of an LC-MS/MS analysis. A variety of polyunsaturated fatty acids were found at higher concentrations in the testes than in the ovaries. 16 s rDNA sequencing analysis showed that the composition and structure of the intestinal microbiota were similar between males and females. These results suggest that sex differences in intestinal metabolism of A. japonicus are not due to differences in the microbiota, and we speculate that gonadal metabolism may be related to intestinal morphology. This information might be useful in improving the reproductive efficiency of sea cucumbers in captivity.

Fishes show remarkably diverse aggressive behaviour. Aggression is expressed to secure resources; adjusting aggression levels according to context is key to avoid negative consequences for fitness and survival. Nonetheless, despite its importance, the physiological basis of aggression in fishes is still poorly understood. Several reports suggest hormonal modulation of aggression, particularly by androgens, but contradictory studies have been published. Studies exploring the role of chemical communication in aggressive behaviour are also scant, and the pheromones involved remain to be unequivocally characterized. This is surprising as chemical communication is the most ancient form of information exchange and plays a variety of other roles in fishes. Furthermore, the study of chemical communication and aggression is relevant at the evolutionary, ecological and economic levels. A few pioneering studies support the hypothesis that aggressive behaviour, at least in some teleosts, is modulated by “dominance pheromones” that reflect the social status of the sender, but there is little information on the identity of the compounds involved. This review aims to provide a global view of aggressive behaviour in fishes and its underlying physiological mechanisms including the involvement of chemical communication, and discusses the potential use of dominance pheromones to improve fish welfare. Methodological considerations and future research directions are also outlined.

The role of hormones as modulators of aggressive behavior in fish remains poorly understood. Androgens and corticosteroids, in particular, have been associated with aggressive behavior in fish but it is still not clear if animals adjust the secretion of these hormones to regulate behavior during ongoing fights, in response to fight outcomes in order to adjust aggressive behavior in subsequent fights, or both. With its stereotyped displays and high aggression levels, the Siamese fighting fish Betta splendens is an excellent model to investigate this question. Here, we compared the behavioral and endocrine response of male B. splendens to fights where there is no winner or loser by presenting them with a size-matched live interacting conspecific behind a transparent partition or with a mirror image. The aggressive response started with threat displays that were overall similar in frequency and duration towards both types of stimuli. Fights transitioned to overt attacks and interacting with a live conspecific elicited a higher frequency of attempted bites and head hits, as compared with the mirror image. There was a pronounced increase in plasma androgens (11-ketotestosterone and testosterone) and corticosteroids (cortisol) levels in response to the aggression challenge, independent of stimulus type. Post-fight intra-group levels of these hormones did not correlate with measures of physical activity or aggressive behavior. A linear discriminant analysis including all behavioral and endocrine data was a poor classifier of fish from the conspecific and mirror trials, showing that overall the behavioral and endocrine response to mirror images and conspecifics was similar. The results show that fight resolution is not necessary to induce an evident increase in peripheral levels of androgens and corticosteroids in B. splendens. However, the function of these hormones during present and future aggressive contests remains to be clarified.

In Southeast Asia, males of the Siamese fighting fish Betta splendens have been selected across centuries for paired-staged fights. During the selection process, matched for size males fight in a small tank until the contest is resolved. Breeders discard losing batches and reproduce winner batches with the aim of increasing fight performance. We assessed the results of this long-term selection process by comparing under standard laboratory conditions male and female aggressive behaviour of one strain selected for staged fights (“fighters”) and one strain of wild-types. The aggressive response of adult fish was tested against their mirror image or a size-matched conspecific. Fighter males were more aggressive than wild-type males for all measured behaviours. Differences were not only quantitative but the pattern of fight display was also divergent. Fighter males had an overall higher swimming activity, performing frequent fast strikes in the direction of the intruder and displaying from a distance. Wild-type males were less active and exhibited aggressive displays mostly in close proximity to the stimuli. Females of the fighter strain, which are not used for fights, were also more aggressive than wild-type females. Aggressive behaviours were correlated across male and female fighter siblings, suggesting common genetic and physiological mechanisms to male and female aggression in this species. The study further shows that results were largely independent of the stimulus type, with the mirror test inducing similar and less variable responses than the live conspecific presentation. These results suggest that selection for male winners co-selected for high-frequency and metabolic demanding aggressive display in males and also enhanced female aggression, opening a wide range of testable hypothesis about the ultimate and proximate mechanisms of male and female aggression in B. splendens.

In southeast Asia, males of the Siamese fighting fish, Betta splendens, have been selected across centuries for winning paired staged fights and previous work has shown that males from fighter strains are more aggressive than wild-types. This strong directional selection for winners is likely to have targeted aggression-related endocrine systems, and a comparison between fighter and wild-type strains can bring into evidence the key hormones implicated in aggression. Here, we compared the plasma levels of the androgen 11-ketotestosterone (KT) and of the corticosteroid cortisol (F) in F2 males of a fighter and a wild-type strain raised under similar laboratory conditions. We show that F was generally lower in fighter as compared with wild-type males, while no overall differences in KT levels were detected between strains. When presented with a mirror-induced aggressive challenge, post-fight levels of F increased but more significantly so in wild-type males, while KT increased in males of both strains. After the challenge, fighter males had higher levels of KT as compared with wild-type males, while the pattern for F was opposite. As compared with animals in social groups, wild-type males placed under social isolation had lower F levels, while KT decreased for fighters. Taken together, this data suggests that while wild-type males responded to aggression with an increase in circulating levels of both androgens and corticosteroids, males selected for winning fights maintained a blunt F response, increasing only KT levels. These data agree with the hypothesis that a combination of high levels of androgens and low levels of corticosteroids is associated with high aggression. Overall, these results seem to indicate that selection for winning had a stronger impact in the hypothalamus-pituitary-interrenal axis than in the hypothalamus-pituitary–gonadal axis in B. splendens.

The occurrence of endocrine disrupting chemicals (EDCs) is a major issue for marine and coastal environments in the proximity of urban areas. The occurrence of EDCs in the Pearl River Delta region is well documented but specific data related to Macao is unavailable. The levels of bisphenol-A (BPA), estrone (E1), 17α-estradiol (αE2), 17β-estradiol (E2), estriol (E3), and 17α-ethynylestradiol (EE2) were measured in sediment samples collected along the coastline of Macao. BPA was found in all 45 collected samples with lower BPA concentrations associated to the presence of mangrove trees. Biodegradation assays were performed to evaluate the capacity of the microbial communities of the surveyed ecosystems to degrade BPA and its analogue BPS. Using sediments collected at a WWTP discharge point as inoculum, at a concentration of 2 mg l−1 complete removal of BPA was observed within 6 days, whereas for the same concentration BPS removal was of 95% after 10 days, which is particularly interesting since this compound is considered recalcitrant to biodegradation and likely to accumulate in the environment. Supplementation with BPA improved the degradation of bisphenol-S (BPS). Aiming at the isolation of EDCs-degrading bacteria, enrichments were established with sediments supplied with BPA, BPS, E2 and EE2, which led to the isolation of a bacterial strain, identified as Rhodoccoccus sp. ED55, able to degrade the four compounds at different extents. The isolated strain represents a valuable candidate for bioremediation of contaminated soils and waters.

The levels of air pollution in Macao often exceeded the levels recommended by WHO. In order for the population to take precautionary measures and avoid further health risks under high pollutant exposure, it is important to develop a reliable air quality forecast. Statistical models based on linear multiple regression (MR) and classification and regression trees (CART) analysis were developed successfully, for Macao, to predict the next day concentrations of NO2, PM10, PM2.5, and O3. All the developed models were statistically significantly valid with a 95% confidence level with high coefficients of determination (from 0.78 to 0.93) for all pollutants. The models utilized meteorological and air quality variables based on 5 years of historical data, from 2013 to 2017. Data from 2013 to 2016 were used to develop the statistical models and data from 2017 was used for validation purposes. A wide range of meteorological and air quality variables was identified, and only some were selected as significant independent variables. Meteorological variables were selected from an extensive list of variables, including geopotential height, relative humidity, atmospheric stability, and air temperature at different vertical levels. Air quality variables translate the resilience of the recent past concentrations of each pollutant and usually are maximum and/or the average of latest 24-h levels. The models were applied in forecasting the next day average daily concentrations for NO2 and PM and maximum hourly O3 levels for five air quality monitoring stations. The results are expected to be an operational air quality forecast for Macao.

Statistical methods such as multiple linear regression (MLR) and classification and regression tree (CART) analysis were used to build prediction models for the levels of pollutant concentrations in Macao using meteorological and air quality historical data to three periods: (i) from 2013 to 2016, (ii) from 2015 to 2018, and (iii) from 2013 to 2018. The variables retained by the models were identical for nitrogen dioxide (NO2), particulate matter (PM10), PM2.5, but not for ozone (O3) Air pollution data from 2019 was used for validation purposes. The model for the 2013 to 2018 period was the one that performed best in prediction of the next-day concentrations levels in 2019, with high coefficient of determination (R2), between predicted and observed daily average concentrations (between 0.78 and 0.89 for all pollutants), and low root mean square error (RMSE), mean absolute error (MAE), and biases (BIAS). To understand if the prediction model was robust to extreme variations in pollutants concentration, a test was performed under the circumstances of a high pollution episode for PM2.5 and O3 during 2019, and the low pollution episode during the period of implementation of the preventive measures for COVID-19 pandemic. Regarding the high pollution episode, the period of the Chinese National Holiday of 2019 was selected, in which high concentration levels were identified for PM2.5 and O3, with peaks of daily concentration exceeding 55 μg/m3 and 400 μg/m3, respectively. The 2013 to 2018 model successfully predicted this high pollution episode with high coefficients of determination (of 0.92 for PM2.5 and 0.82 for O3). The low pollution episode for PM2.5 and O3 was identified during the 2020 COVID-19 pandemic period, with a low record of daily concentration for PM2.5 levels at 2 μg/m3 and O3 levels at 50 μg/m3, respectively. The 2013 to 2018 model successfully predicted the low pollution episode for PM2.5 and O3 with a high coefficient of determination (0.86 and 0.84, respectively). Overall, the results demonstrate that the statistical forecast model is robust and able to correctly reproduce extreme air pollution events of both high and low concentration levels.

Air pollution is a major concern issue on Macao since the concentration levels of several of the most common pollutants are frequently above the internationally recommended values. The low air quality episodes impacts on human health paired with highly populated urban areas are important motivations to develop forecast methodologies in order to anticipate pollution episodes, allowing establishing warnings to the local community to take precautionary measures and avoid outdoor activities during this period. Using statistical methods (multiple linear regression (MLR) and classification and regression tree (CART) analysis) we were able to develop forecasting models for the main pollutants (NO2, PM2.5, and O3) enabling us to know the next day concentrations with a good skill, translated by high coefficients of determination (0.82–0.90) on a 95% confidence level. The model development was based on six years of historical data, 2013 to 2018, consisting of surface and upper-air meteorological observations and surface air quality observations. The year of 2019 was used for model validation. From an initially large group of meteorological and air quality variables only a few were identified as significant dependent variables in the model. The selected meteorological variables included geopotential height, relative humidity and air temperature at different altitude levels and atmospheric stability characterization parameters. The air quality predictors used included recent past hourly levels of mean concentrations for NO2 and PM2.5 and maximum concentrations for O3. The application of the obtained models provides the expected daily mean concentrations for NO2 and PM2.5 and maximum hourly concentrations O3 for the next day in Taipa Ambient air quality monitoring stations. The described methodology is now operational, in Macao, since 2020.

The levels of air pollution in Macao often exceeded the levels recommended by WHO. In order for the population to take precautionary measures and avoid further health risks under high pollutant exposure, it is important to develop a reliable air quality forecast. Statistical models based on multiple regression (MR) analysis were developed successfully for Macao to predict the next day concentrations of PM10, PM2.5, and NO2. All the developed models were statistically significantly valid with a 95% confidence level with high coefficients of determination (from 0.89 to 0.92) for all pollutants. The models utilized meteorological and air quality variables based on five years of historical data, from 2013 to 2017. The data from 2013 to 2016 were used to develop the statistical models and data from 2017 were used for validation purposes. A wide range of meteorological and air quality variables were identified, and only some were selected as significant dependent variables. Meteorological variables were selected from an extensive list of variables, including geopotential height, relative humidity, atmospheric stability, and air temperature at different vertical levels. Air quality variables translate the resilience of the recent past concentrations of each pollutant and usually are maximum and/or the average of latest 24-hour levels. The models were applied in forecasting the next day average daily concentrations for PM10, PM2.5, and NO2 for the air quality monitoring stations. The results are expected to be an operational air quality forecast for Macao.