Classification and distribution of freshwater microplastics along the Italian Po river by hyperspectral imaging.
Ontology highlight
ABSTRACT:
SUBMITTER: Fiore L
PROVIDER: S-EPMC9252960 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Microplastics result from fragmentation of plastic debris or are released to the environment as pre-production pellets or components of consumer and industrial products. In the oceans, they contribute to the 'great garbage patches'. They are ingested by many organisms, from protozoa to baleen whales, and pose a threat to the aquatic fauna. Although as much as 80% of marine debris originates from land, little attention was given to the role of rivers as debris pathways to the sea. Worldwide, not a single great river has yet been studied for the surface microplastics load over its length. We report the abundance and composition of microplastics at the surface of the Rhine, one of the largest European rivers. Measurements were made at 11 locations over a stretch of 820 km. Microplastics were found in all samples, with 892,777 particles km (-2) on average. In the Rhine-Ruhr metropolitan area, a peak concentration of 3.9 million particles km (-2) was measured. Microplastics concentrations were diverse along and across the river, reflecting various sources and sinks such as waste water treatment plants, tributaries and weirs. Measures should be implemented to avoid and reduce the pollution with anthropogenic litter in aquatic ecosystems.
| S-EPMC4672315 | biostudies-literature
Project description:BackgroundDinoflagellates have the potential to pose severe ecological and economic damages to aquatic ecosystems. It is therefore largely needed to understand the causes and consequences of distribution patterns of dinoflagellate communities in order to manage potential environmental problems. However, a majority of studies have focused on marine ecosystems, while the geographical distribution patterns of dinoflagellate communities and associated determinants in freshwater ecosystems remain unexplored, particularly in running water ecosystems such as rivers and streams.MethodsHere we utilized multiple linear regression analysis and combined information on species composition recovered by high-throughput sequencing and spatial and environmental variables to analyze the distribution patterns of dinoflagellate communities along the Songhua River.ResultsAfter high-throughput sequencing, a total of 490 operational taxonomic units (OTUs) were assigned to dinoflagellates, covering seven orders, 13 families and 22 genera. Although the sample sites were grouped into three distinctive clusters with significant difference (p < 0.05) in environmental variables, OTUs-based dinoflagellate communities among the three clusters showed no significant difference (p > 0.05). Among all 24 environmental factors, two environmental variables, including NO3-N and total dissolved solids (TDS), were selected as the significantly influential factors (p < 0.05) on the distribution patterns of dinoflagellate communities based on forward selection. The redundancy analysis (RDA) model showed that only a small proportion of community variation (6.1%) could be explained by both environmental (NO3-N and TDS) and dispersal predictors (watercourse distance) along the River. Variance partitioning revealed a larger contribution of local environmental factors (5.85%) than dispersal (0.50%) to the total variation of dinoflagellate communities.DiscussionOur findings indicated that in addition to the two quantifiable processes in this study (species sorting and dispersal), more unquantifiable stochastic processes such as temporal extinction and colonization events due to rainfall may be responsible for the observed geographical distribution of the dinoflagellate community along the Songhua River. Results obtained in this study suggested that deeper investigations covering different seasons are needed to understand the causes and consequences of geographical distribution patterns of dinoflagellate biodiversity in river ecosystems.
| S-EPMC6461062 | biostudies-literature
Project description:The type and extent of microplastic contamination in water and sediment of Haraz River were evaluated. Water and sediment samples were collected using a planktonic trawl with a mesh size of 300 µ and a Van Veen grab, from February to May 2017. The morphology and elemental compounds of microplastic particles were analysed using SEM/EDX. Moreover, differential scanning calorimetry (DSC) was done for polymers identification; so that the data could be used for comparative analyses. The number of pieces per kg dry weight in sediments and per cubic meter sampled water was determined. Last but not least, plastic types were also distinguished.
| S-EPMC7452695 | biostudies-literature
Project description:Despite the importance of bacteria in aquatic ecosystems and their predictable diversity patterns across space and time, biomonitoring tools for status assessment relying on these organisms are widely lacking. This is partly due to insufficient data and models to identify reliable microbial predictors. Here, we show metabarcoding in combination with multivariate statistics and machine learning allows to identify bacterial bioindicators for existing biological status classification systems. Bacterial beta-diversity dynamics follow environmental gradients and the observed associations highlight potential bioindicators for ecological outcomes. Spatio-temporal links spanning the microbial communities along the river allow accurate prediction of downstream biological status from upstream information. Network analysis on amplicon sequence veariants identify as good indicators genera Fluviicola, Acinetobacter, Flavobacterium, and Rhodoluna, and reveal informational redundancy among taxa, which coincides with taxonomic relatedness. The redundancy among bacterial bioindicators reveals mutually exclusive taxa, which allow accurate biological status modeling using as few as 2-3 amplicon sequence variants. As such our models show that using a few bacterial amplicon sequence variants from globally distributed genera allows for biological status assessment along river systems.
| S-EPMC10439154 | biostudies-literature
Project description:Understanding of the sources, fate, and impact of microplastics (MPs, < 5 mm) remains limited, particularly in freshwater environments, while limited comparability across available surveys hinders adequate monitoring and risk assessment of these contaminants. Here, the distribution of microscopic debris in an urban river close to the marine environment in the West of Scotland was investigated to assess concentration and distribution of primary and secondary MPs. Also, the efficiency of light and scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS) was evaluated for characterisation and quantification of MPs sized 2.8 mm-11 μm. Bank sediment samples were collected twice from the River Kelvin in Glasgow and were size-fractionated and processed for extraction of MPs by density separation. Sample MPs spiking and use of procedural blanks allowed the influence of processing on field data quality to be considered. Total abundances were 161-432 MPs kg-1 dry sediment, with fibres as the dominant type, comprising > 88% of total counts. Nevertheless, fibres in blanks suggest potential contributions from atmospheric contamination. Moreover, fibres concentrated mainly in fractions < 0.09 mm suggesting that their fate may be influenced by drivers of fine sediment dynamics in rivers. While no primary MPs were observed, metallic and glass pellets were present in high abundances in settled material and could be easily misidentified by visual inspection, demonstrating that compositional analysis is needed to avoid analytical errors from MP misidentification and overestimation. SEM-EDS allowed for a quick screening of plastic vs non-plastic pellets and improved identification of smaller fragments, whereas more advanced techniques are needed for proper identification of fibres. This study is the first to report on MPs in freshwater rivers in Scotland and suggests that diffuse sources of pollution may be delivering secondary MPs to the river. Their sources, fate, and risk in these systems will thus warrant further attention.
| S-EPMC6476856 | biostudies-literature
Project description:Many studies have recently used several deep learning methods for detecting skin cancer. However, hyperspectral imaging (HSI) is a noninvasive optics system that can obtain wavelength information on the location of skin cancer lesions and requires further investigation. Hyperspectral technology can capture hundreds of narrow bands of the electromagnetic spectrum both within and outside the visible wavelength range as well as bands that enhance the distinction of image features. The dataset from the ISIC library was used in this study to detect and classify skin cancer on the basis of basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and seborrheic keratosis (SK). The dataset was divided into training and test sets, and you only look once (YOLO) version 5 was applied to train the model. The model performance was judged according to the generated confusion matrix and five indicating parameters, including precision, recall, specificity, accuracy, and the F1-score of the trained model. Two models, namely, hyperspectral narrowband image (HSI-NBI) and RGB classification, were built and then compared in this study to understand the performance of HSI with the RGB model. Experimental results showed that the HSI model can learn the SCC feature better than the original RGB image because the feature is more prominent or the model is not captured in other categories. The recall rate of the RGB and HSI models were 0.722 to 0.794, respectively, thereby indicating an overall increase of 7.5% when using the HSI model.
| S-EPMC9918106 | biostudies-literature
Project description:We aimed to determine the presence of Ixodes ricinusticks in heavily populated areas of the Po River Valley after report of a Lyme disease case. Eighteen percent of ticks examined from 3 locations were positive for Lyme disease borreliae. Lyme disease was diagnosed for 3 workers at risk for tick bite.
| S-EPMC3298309 | biostudies-literature
Project description:Analysis of microplastics (MP) in environmental samples is an emerging field, which is performed with various methods and instruments based either on spectroscopy or thermoanalytical methods. In general, both approaches result in two different types of data sets that are either mass or particle number related. Depending on detection limits of the respective method and instrumentation the derived polymer composition trends may vary. In this study, we compare the results of hyperspectral Fourier-transform infrared (FTIR) imaging analysis and pyrolysis gas chromatography-mass spectrometry (Py-GC/MS) analysis performed on a set of environmental samples that differ in complexity and degree of microplastic contamination. The measurements were conducted consecutively, and on exactly the same sample. First, the samples were investigated with FTIR using aluminum oxide filters; subsequently, these were crushed, transferred to glass fiber filters, in pyrolysis cups, and measured via Py-GC/MS. After a general data harmonization step, the trends in MP contamination were thoroughly investigated with regard to the respective sample set and the derived polymer compositions. While the overall trends in MP contamination were very similar, differences were observed in the polymer compositions. Furthermore, polymer masses were empirically calculated from FTIR data and compared with the Py-GC/MS results. Here, a most plausible shape-related overestimation of the calculated polymer masses was observed in samples with larger particles and increased particle numbers. Taking into account the different measurement principles of both methods, all results were examined and discussed, and future needs for harmonization of intermethodological results were identified and highlighted. Graphical abstract.
| S-EPMC7680748 | biostudies-literature
Project description:Microscopy and omics are complementary approaches to probe the molecular state of cells in health and disease, combining granularity with scalability. While important advances have been achieved over the last decade in each area, integrating both imaging- and sequencing-based assays on the same cell has proven challenging. In this study, a new approach called HyperSeq that combines hyperspectral autofluorescence imaging with transcriptomics on the same cell is demonstrated. HyperSeq was applied to Michigan Cancer Foundation 7 (MCF-7) breast cancer cells and identified a subpopulation of cells exhibiting bright autofluorescence rings at the plasma membrane in optical channel 13 (ex = 431 nm, em = 594 nm). Correlating the presence of a ring with the gene expression in the same cell indicated that ringed cells are more likely to express hallmark genes of apoptosis and gene silencing and less likely to express genes associated with ATP production. Further, correlation of cell morphology with gene expression suggested that multiple members of the spliceosome were upregulated in larger cells. A number of genes, albeit evenly expressed across cell sizes, exhibited higher usage of specific exons in larger or smaller cells. Finally, correlation between gene expression and fluorescence within the spectral range of Nicotinamide adenine dinucleotide hydrogen (NADH) provided preliminary insight into the metabolic states of cells. These observations provided a link between the cell’s optical spectrum and its internal molecular state, demonstrating the utility of HyperSeq to study cell biology at single cell resolution by integrating spectral, morphological and transcriptomic analyses into a single, streamlined workflow.
2024-02-05 | GSE254034 | GEO
Project description:Blastocystis is a common zoonotic enteric protozoan that has been classified into 17 distinct subtypes (STs). A cross-sectional study was conducted to determine the prevalence and subtype distributions of Blastocystis in villagers living along the Chao Phraya River, Ayutthaya Province, Thailand, and to assess the risk of zoonotic infection. In total, 220 stool samples were collected, and DNA was extracted. PCR and sequencing were performed with primers targeting the small-subunit ribosomal RNA (SSU rRNA) genes. Blastocystis was present in 5.9% (13/220) of samples, and ST3 (5.0%; 11/220) was the predominant subtype, followed by ST2 (0.45%; 1/220) and ST6 (0.45%; 1/220). Phylogenetic trees were constructed with the maximum-likelihood method based on the Hasegawa-Kishino-Yano + G + I model, neighbor-joining, and maximum parsimony methods. The percentage of bootstrapped trees in which the associated taxa clustered together was relatively high. All the sequences of the Blastocystis-positive samples (KU051524-KU051536) were closely related to those from animals (pig, cattle, and chicken), indicating a zoonotic risk. Therefore, the villagers require proper health education, especially regarding the prevention of parasitic infection, to improve their personal hygiene and community health. Further studies are required to investigate the Blastocystis STs in the animals living in these villages.
| S-EPMC5040084 | biostudies-literature