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Результаты 1561-1570 из 6,560
Responses of an old and a modern Indian wheat cultivar to future O3 level: Physiological, yield and grain quality parameters Полный текст
2020
A field study was conducted to understand the physiological responses, yield and grain quality of an old (HUW234) and a modern (HD3118) wheat cultivar exposed to elevated ozone (O₃). The cultivars were grown under ambient O₃ (NF) and ambient +20 ppb O₃ (NF+) conditions using open-top chambers (OTCs). The comparative study of an old and a modern cultivar showed variable physiological responses under elevated O₃ exposure. Elevated O₃ in old cultivar caused high reductions in Rubisco activity (Vcₘₐₓ) and electron transport rate (J) compared to modern cultivar with simultaneous reductions in the rate of photosynthesis and chlorophyll fluorescence. In modern cultivar, high stomatal density and conductance caused higher O₃ uptake thereby triggering more damage to the adjacent stomatal cells and photosynthetic pigments coupled with reductions in photosynthetic rate and photosynthetic nitrogen use efficiency (PNUE). Modern cultivar also showed relatively high reduction in grain yield compared to old one under NF + treatment. Furthermore, grain quality traits (such as starch, protein and amino acids) of modern cultivar were better than old cultivar under ambient O₃, but showed more deterioration under NF + treatment. Results thus indicated that modern cultivar is relatively more susceptible to O₃ and showed more negative impacts on plant performance, yield and quality of grains compared to old cultivar.
Показать больше [+] Меньше [-]The influence of salinization on seed germination and plant growth under mono and polyculture Полный текст
2020
Sea level rise induced-salinization is lowering coastal soils productivity. In order to assess the effects that increased salinity may provoke in terrestrial plants, using as model species: Trifolium pratense, Lolium perenne, Festuca arundinacea and Vicia sativa, two specific objectives were targeted: i) to determine the sensitivity of the selected plant species to increased salinity (induced by seawater-SW or by NaCl, proposed as a surrogate of SW) and, ii) to assess the influence of salinization in total biomass under different agricultural practices (mono- or polycultures).The four plant species exhibited a higher sensitivity to NaCl than to SW. Festuca arundinacea was the most tolerant species to NaCl (EC₅₀,ₛₑₑd gₑᵣₘᵢₙₐₜᵢₒₙ and EC₅₀,gᵣₒwₜₕ of 18.6 and 10.5 mScm⁻¹, respectively). The other three species presented effective conductivities in the same order of magnitude and, in general, with 95% confidence limits overlapping. Soil moistened with SW caused no significant adverse effects on seed germination and growth of L. perenne. Similar to NaCl, the other three species, in general, presented a similar sensitivity to SW exposure with EC₅₀,ₛₑₑd gₑᵣₘᵢₙₐₜᵢₒₙ and EC₅₀,gᵣₒwₜₕ within the same order of magnitude and with confidence limits overlapping.The agricultural practice (mono-vs polyculture) showed some influence on the biomass of each plant species. When considering total productivity, for aerial and root biomass, it was higher in control comparatively to salinization conditions. Under salinization stress, the practice of polyculture was associated with a higher aerial and root total biomass than monocultures (for instance with combinations with T. pratense and F. arundinacea).Results suggest that the effects of salinity stress on total productivity may be minimized under agricultural practices of polyculture. Thus, this type of cultures should be encouraged in low-lying coastal ecosystems that are predicted to suffer from salinization caused by seawater intrusions.
Показать больше [+] Меньше [-]A three-phase-successive partition-limited model to predict plant accumulation of organic contaminants from soils treated with surfactants Полный текст
2020
The application of surfactants is an effective way to inhibit the migration of organic contaminants (OCs) from soil to plants, and thus would be a great candidate method for producing safe agricultural products in organic-contaminated farmland. In this study, it was found that cetyltrimethyl ammonium bromide (CTMAB) reduced the OCs in cabbage by 22.0–64.1%, and those in lettuce by 18.8–36.5%. We developed a mathematical model to predict the accumulation of OCs in plants in the presence of surfactants. The successive partitioning of OCs among three phases, namely, soil, soil water and plant roots, was considered. The equilibrium of OC between the soil and soil water was scaled using the sorption coefficient of OCs on soils normalized by the soil organic carbon (Kₒc) and carbon-normalized OCs sorption coefficient with the sorbed surfactants (Kₛₛ). To precisely calculate the Kₒc and Kₛₛ, the bioavailable and bound OCs were measured using a sequential extraction method. Linear positive correlations between the logarithm of Kₒc (or Kₛₛ) and the logarithm of the octanol-water partition coefficient (log Kₒw) of OCs were established for laterite soils, paddy soils and black soils. In the presence of CTMAB, the equilibrium of OCs between the soil water and plant roots was scaled using the carbon-normalized OC sorption coefficient with the sorbed surfactants (Kₛf), whose logarithmic value was linearly correlated with the log Kₒw of the OCs. A three-phase-successive partition-limited model was developed based on these relationships, demonstrating an average prediction accuracy of 76.6 ± 36.8%. Our results indicated that the decrease in bioavailable OCs in soils and the increase in sorption of OCs on roots should be taken into consideration when predicting plant uptake. This research provides a validated mathematical model for predicting the concentration of OCs in plants in the presence of surfactants.
Показать больше [+] Меньше [-]Associations between persistent organic pollutants and endometriosis: A multipollutant assessment using machine learning algorithms Полный текст
2020
Associations between persistent organic pollutants and endometriosis: A multipollutant assessment using machine learning algorithms Полный текст
2020
Endometriosis is a gynaecological disease characterised by the presence of endometriotic tissue outside of the uterus impacting a significant fraction of women of childbearing age. Evidence from epidemiological studies suggests a relationship between risk of endometriosis and exposure to some organochlorine persistent organic pollutants (POPs). However, these chemicals are numerous and occur in complex and highly correlated mixtures, and to date, most studies have not accounted for this simultaneous exposure. Linear and logistic regression models are constrained to adjusting for multiple exposures when variables are highly intercorrelated, resulting in unstable coefficients and arbitrary findings. Advanced machine learning models, of emerging use in epidemiology, today appear as a promising option to address these limitations. In this study, different machine learning techniques were compared on a dataset from a case-control study conducted in France to explore associations between mixtures of POPs and deep endometriosis. The battery of models encompassed regularised logistic regression, artificial neural network, support vector machine, adaptive boosting, and partial least-squares discriminant analysis with some additional sparsity constraints. These techniques were applied to identify the biomarkers of internal exposure in adipose tissue most associated with endometriosis and to compare model classification performance. The five tested models revealed a consistent selection of most associated POPs with deep endometriosis, including octachlorodibenzofuran, cis-heptachlor epoxide, polychlorinated biphenyl 77 or trans-nonachlor, among others. The high classification performance of all five models confirmed that machine learning may be a promising complementary approach in modelling highly correlated exposure biomarkers and their associations with health outcomes. Regularised logistic regression provided a good compromise between the interpretability of traditional statistical approaches and the classification capacity of machine learning approaches. Applying a battery of complementary algorithms may be a strategic approach to decipher complex exposome-health associations when the underlying structure is unknown.
Показать больше [+] Меньше [-]Associations between persistent organic pollutants and endometriosis: A multipollutant assessment using machine learning algorithms Полный текст
2020
Matta, Komodo | Vigneau, Evelyne | Cariou, Véronique | Mouret, Delphine | Ploteau, Stéphane | Le Bizec, Bruno | Antignac, Jean-Philippe | Cano-Sancho, Germán | Laboratoire d'étude des Résidus et Contaminants dans les Aliments (LABERCA) ; École nationale vétérinaire, agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Statistique, Sensométrie et Chimiométrie (StatSC) ; École nationale vétérinaire, agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Centre hospitalier universitaire de Nantes (CHU Nantes)
International audience
Показать больше [+] Меньше [-]Whole-transcriptome analysis of the toxic effects of zearalenone exposure on ceRNA networks in porcine granulosa cells Полный текст
2020
Zearalenone (ZEA), an estrogen-like mycotoxin, is commonly detected in animal feeds including improperly stored grains. It has been well demonstrated that ovarian granulosa cells (GCs) perform vital roles during follicular development, however, the competing endogenous RNA (ceRNA) network in GCs after ZEA exposure remains to be well described. Here, for the first time, we adopted whole-transcriptome sequence technology to explore the molecular mechanism of ZEA toxicology on porcine GCs. The results provide evidence that the cell cycle of porcine GCs is arrested in the G2/M phase after exposure to ZEA. Furthermore, bioinformation analysis found that cell cycle arrest related genes were perturbed, including CDK1, CCNB1, CDC25A, and CDC25C, which was consistent with the results of RT-qPCR, immunofluorescence, and Western Blotting. Based on the whole-transcriptome sequence data, by constructing ceRNA networks related to cell cycle arrest, we observed that ZEA exposure arrested cell cycle progression at the G2/M phase in porcine GCs, and non-coding RNAs (ncRNAs) played an important role in this process via regulating the expressions of cell cycle arrest related genes. Taken together, our data here provides strong data to support that the toxicological mechanism regarding the widely distributed toxicant ZEA acts through ceRNA networks in porcine granulosa cells.
Показать больше [+] Меньше [-]Foraminifera as bioindicators of water quality: The FoRAM Index revisited Полный текст
2020
Prazeres, Martina | Martínez-Colón, Michael | Muller, Pamela Hallock
Coral reefs worldwide are degrading at alarming rates due to local and global stressors. There are ongoing needs for bioindicator systems that can be used to assess reef health status, the potential for recovery following destructive events such as tropical storms, and for the success of coral transplants. Benthic foraminiferal shells are ubiquitous components of carbonate sediment in reef environments that can be sampled at minimal cost and environmental impact. Here we review the development and application of the FoRAM Index (FI), which provides a bioindicator metric for water quality that supports reef accretion. We outline the strengths and limitations of the FI, and propose how it can be applied more effectively across different geographical regions.
Показать больше [+] Меньше [-]Who’s better at spotting? A comparison between aerial photography and observer-based methods to monitor floating marine litter and marine mega-fauna Полный текст
2020
Garcia-Garin, Odei | Aguilar, Alex | Borrell, Asunción | Gozalbes, Patricia | Lobo, Agustín | Penadés-Suay, Jaime | Raga, Juan A. | Revuelta, Ohiana | Serrano, María | Vighi, Morgana
Who’s better at spotting? A comparison between aerial photography and observer-based methods to monitor floating marine litter and marine mega-fauna Полный текст
2020
Garcia-Garin, Odei | Aguilar, Alex | Borrell, Asunción | Gozalbes, Patricia | Lobo, Agustín | Penadés-Suay, Jaime | Raga, Juan A. | Revuelta, Ohiana | Serrano, María | Vighi, Morgana
Pollution by marine litter is raising major concerns due to its potential impact on marine biodiversity and, above all, on endangered mega-fauna species, such as cetaceans and sea turtles. The density and distribution of marine litter and mega-fauna have been traditionally monitored through observer-based methods, yet the advent of new technologies has introduced aerial photography as an alternative monitoring method. However, to integrate results produced by different monitoring techniques and consider the photographic method a viable alternative, this ‘new’ methodology must be validated. This study aims to compare observations obtained from the concurrent application of observer-based and photographic methods during aerial surveys. To do so, a Partenavia P-68 aircraft equipped with an RGB sensor was used to monitor the waters off the Spanish Mediterranean coast along 12 transects (941 km). Over 10000 images were collected and checked manually by a photo-interpreter to detect potential targets, which were classified as floating marine macro-litter, mega-fauna and seabirds. The two methods allowed the detection of items from the three categories and proved equally effective for the detection of cetaceans, sea turtles and large fish on the sea surface. However, the photographic method was more effective for floating litter detection and the observer-based method was more effective for seabird detection. These results provide the first validation of the use of aerial photography to monitor floating litter and mega-fauna over the marine surface.
Показать больше [+] Меньше [-]Who's better at spotting? Comparison between aerial photography and visual methods to monitor floating marine litter and marine mega-fauna Полный текст
2020
Garcia-Garin, Odei | Aguilar, Àlex | Borrell Thió, Assumpció | Gozalbes, Patricia | Lobo, Agustín | Raga, Juan A. | Revuelta, Ohiana | Serrano, Maria | Vighi, Morgana
Pollution by marine litter is raising major concerns due to its potential impact on marine biodiversity and, above all, on endangered mega-fauna species, such as cetaceans and sea turtles. The density and distribution of marine litter and mega-fauna have been traditionally monitored through observer-based methods, yet the advent of new technologies has introduced aerial photography as an alternative monitoring method. However, to integrate results produced by different monitoring techniques and consider the photographic method a viable alternative, this 'new' methodology must be validated. This study aims to compare observations obtained from the concurrent application of observer-based and photographic methods during aerial surveys. To do so, a Partenavia P-68 aircraft equipped with an RGB sensor was used to monitor the waters off the Spanish Mediterranean coast along 12 transects (941 km). Over 10000 images were collected and checked manually by a photo-interpreter to detect potential targets, which were classified as floating marine macro-litter, mega-fauna and seabirds. The two methods allowed the detection of items from the three categories and proved equally effective for the detection of cetaceans, sea turtles and large fish on the sea surface. However, the photographic method was more effective for floating litter detection and the observer-based method was more effective for seabird detection. These results provide the first validation of the use of aerial photography to monitor floating litter and mega-fauna over the marine surface.
Показать больше [+] Меньше [-]A hybrid air pollutant concentration prediction model combining secondary decomposition and sequence reconstruction Полный текст
2020
Sun, Wei | Huang, Chenchen
Acid rain is a serious threat to terrestrial ecosystems. To provide more accurate early warning information for acid rain prevention, urban planning, and travel planning, a novel air pollutant prediction model was proposed in this paper to predict NO₂ and SO₂. First, the data were decomposed into several sub-sequences by a complete ensemble empirical mode decomposition with adaptive noise. Second, the subsequences are reconstructed by variational mode decomposition and sample entropy. Then, the new subsequences are predicted by the extreme learning machine combined with the whale optimization algorithm. The empirical analysis was carried out through 8 data sets. According to the experimental results, three main conclusions can be drawn. First, the proposed model in this paper has excellent prediction performance and robustness. In all the comparison experiments, the R² and RMSE of the proposed model are the best among all the models. Second, data preprocessing is very necessary. After adding the decomposition algorithm, the average improvement levels of R² and RMSE were 897.57% and 50.78%, respectively. Third, the re-decomposition of IMF1 is an effective method to improve prediction accuracy. After the re-decomposition of IMF1, R² can be improved by 13.64% on average on the original basis, and RMSE can be reduced by 31.99% on average. The results of this study can provide a valuable reference for the research of air pollutant prediction. In future work, the application of the proposed model in other air pollutants or other regions can be explored.
Показать больше [+] Меньше [-]Occurrence and trophic transfer of per- and polyfluoroalkyl substances in an Antarctic ecosystem Полный текст
2020
Gao, Ke | Miao, Xing | Fu, Jie | Chen, Yu | Li, Huijuan | Pan, Wenxiao | Fu, Jianjie | Zhang, Qinghua | Zhang, Aiqian | Jiang, Guibin
Information on the occurrence and trophodynamics of per- and polyfluoroalkyl substances (PFASs) in the Antarctic region is limited. We investigated the occurrence of PFASs in an ecosystem in the Fildes Peninsula at King George Island and Ardley Island, Antarctica. The profiles, spatial distribution, and trophic transfer behavior of PFASs were further studied. ∑PFASs ranged from 0.50 ± 38.0 ng/g dw (dry weight) in algae to 4.97 ± 1.17 ng/g dw in Neogastropoda (Ngas), which was lower than those in the low- and mid-latitude regions and even Arctic regions. Perfluorobutyric acid (PFBA) was predominant with detection frequencies above 50% in all types of samples, and the relative contribution of PFBA ranged from 22% to 57% in the biota samples. The biomagnification factors of PFBA, perfluoroheptanoate (PFHpA), perfluorohexane sulfonate (PFHxS), and perfluorooctane sulfonate (PFOS) between Archaeogastropoda (Agas) and Ngas were 0.67 ± 0.54, 0.77 ± 0.38, 1.04 ± 1.56, 3.30 ± 4.07, and 1.61 ± 0.89, respectively. The trophic magnification factors of PFHxS and PFOS were 2.09 and 2.92, respectively, which indicated that they could be biomagnified through the food chain. Considering the increasing production and uncertain toxicological risks of emerging PFASs and the sensitive ecosystems in Antarctic regions, more attention should be paid, especially for the short-chain ones in the Antarctic region.
Показать больше [+] Меньше [-]Airborne toluene exposure causes germline apoptosis and neuronal damage that promotes neurobehavioural changes in Caenorhabditis elegans Полный текст
2020
Soares, Marcell Valandro | Charão, Mariele Feiffer | Jacques, Mauricio Tavares | dos Santos, Ana Laura Anibaletto | Luchese, Cristiane | Pinton, Simone | Ávila, Daiana Silva
Toluene is a highly volatile organic solvent present in gasoline. Exposure mainly occurs by absorption via the pulmonary tract and easily reaches the central nervous system, which causes toxic effects. Toluene toxicity has been described but not well established. The present work aimed to evaluate the effects of airborne exposure to toluene, the in vivo model Caenorhabditis elegans was assessed to determine whether nematode could be used to evaluate the effects of exposure to toluene and the possible mechanisms of toxicity of the solvent. Worms at the first or fourth larval stages were exposed to toluene for 48 or 24 h, respectively, in a laboratory-developed vapor chamber at concentrations of 450, 850, 1250 and 1800 ppm. We observed increases in worm mortality and significant developmental delays that occurred in a concentration-dependent manner. An increased incidence of apoptotic events in treated germline cells was shown, which was consistent with observed reductions in reproductive capacity. In addition, toluene promoted significant behavioural changes affecting swimming movements and radial locomotion, which were associated with changes in the fluorescence intensity and morphology of GABAergic and cholinergic neurons. We conclude that toluene exposure was toxic to C. elegans, with effects produced by the induction of apoptosis and neuronal damage.
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